Wireless High Voltage Energy Transmission Drones.
by Michael Feuerstein and Open AI Chat GPT.
Everything is science fiction until it’s not. Every technology is a fantasy and a dream until it’s not.
This is the story of me, putting in research articles written by MIT and combining them with other research articles, and putting them into Open AI Chat GPT (no human error). The purpose was to try to create a wireless transmission system using drones. This is what it provided. What is your opinion? More will be added, in regards to code and parts and what the code concepts are. thank you for taking the time to read this. it has been weeks of conversation in order to generate this original article co-written by AI.
Introduction.
A wireless energy transmission system using quad-rotor drones is a cutting-edge concept that aims to revolutionize the way energy is transmitted and distributed. The concept of using drones as energy transmitters is based on the idea of using the technology to bring energy to remote or hard-to-reach areas that traditional power lines and cables cannot reach.
The need for this system arises from the growing demand for energy in remote communities and in emergency situations where traditional energy sources are unavailable or damaged. This can include disaster-stricken areas, remote villages, and other off-grid locations. In such situations, people are often left without access to electricity, which can cause significant hardship and disrupt their daily lives.
The aim and objectives of this technology are to provide communities and individuals with a reliable source of energy during times of crisis and to help meet their basic energy needs. By using drones as wireless energy transmitters, the system can be rapidly deployed in emergency situations and can fly out to affected areas and immediately start transmitting energy. This is a significant advantage over traditional energy transmission systems, which often require repair and maintenance work before they can function again.
The wireless energy transmission system consists of a network of quadrotor drones, each equipped with specialized equipment for energy transmission, such as a rectenna, which converts radio frequency signals into usable electrical energy. The drones are also equipped with sensors and cameras, such as GPS and distance sensors, to allow for automated navigation and flight control. The drones are controlled via a remote control, which in this case would be a VR/AR headset, allowing for a more immersive and intuitive flight experience. The drones would also have an automated system, which would control the flight based on the distance from the ground and the GPS location.
In conclusion, the proposed wireless energy transmission system, utilizing a network of quad-rotor drones, offers a revolutionary approach to providing power to communities and homes. It provides a flexible and adaptable system that can be rapidly deployed in emergency situations, and it eliminates the need for traditional power lines and cables. This technology is a step towards a more sustainable future by using wasted energy from RF sources and reducing the dependence on fossil fuels.
Wireless Energy Transmission System Using Quad Rotor Drones
Introduction:
The advancement in technology has resulted in the creation of new and innovative systems that aim to improve the lives of people, especially in areas where access to electricity is limited or non-existent. One such technology is the wireless energy transmission system using quad-rotor drones. This system aims to provide a solution for the electrification of remote or disaster-stricken areas.
Purpose:
The primary purpose of the wireless energy transmission system is to provide access to electricity to communities that are in need of it, particularly in crisis or disaster-stricken areas. The system uses quad rotor drones to fly over such areas and provide a source of power. The drones are equipped with the necessary components and systems to collect, store, and transmit electrical energy wirelessly to the ground. The energy transmitted can be used to power a variety of devices such as medical equipment, communication devices, and lighting.
Design:
The quad-rotor drone used in the wireless energy transmission system is designed to be compact, lightweight, and durable. It is equipped with four rotors that provide lift and stability during flight. The size of the drone depends on the amount of energy it needs to store and transmit. The drone is also equipped with a battery that provides the energy needed for flight and for the transmission of electricity.
The number and type of rotors used on the drone are crucial to its performance and stability. The use of four rotors provides a balanced and stable platform for the drone to operate on, which is essential for the successful transmission of electricity. The size of the drone is also a critical factor as it affects the amount of energy that can be stored and transmitted. The drone's battery requirements are determined based on the duration of the flight, the amount of energy stored, and the transmission range.
Conclusion:
The wireless energy transmission system using quad-rotor drones is a promising technology that has the potential to revolutionize the way communities access electricity, particularly in crisis or disaster-stricken areas. The system's design, which includes the use of compact and lightweight quad-rotor drones, makes it an efficient and effective solution for the electrification of remote areas. The system's ability to fly over such areas and provide a source of power can have a significant impact on the lives of people and help in the recovery of communities affected by disasters.
The closed-form toroidal propeller is a unique design that offers several advantages over traditional propellers. This type of propeller consists of two blades that loop together so that the tip of one blade curves back into the other. This closed-form structure minimizes the drag effects of the vortices created at the tips of blades, reducing the amount of energy required for the drone to fly. Additionally, the closed-form structure strengthens the overall stiffness of the propeller, making it less likely to bend or break during operation.
The use of sensors and cameras is crucial for the automated navigation and flight control of quad-rotor drones. These components help to ensure that the drone stays on course, avoids obstacles, and performs its designated tasks safely and efficiently. Some of the most commonly used sensors include GPS, accelerometers, and gyroscopes. These sensors provide the drone with information about its position, speed, and orientation in space.
Cameras are also a key component of the drone's flight control system. They provide the drone with real-time visual information about its surroundings, allowing it to detect and avoid obstacles in its path. Other cameras, such as thermal cameras, can be used to detect heat signatures and help to guide the drone to its target.
The integration of these various sensors and cameras allows the drone to perform highly complex tasks with a high degree of accuracy and reliability. These capabilities make the wireless energy transmission system using quad-rotor drones a highly useful tool for a variety of applications, including disaster relief and humanitarian aid. With its ability to fly out and immediately transmit energy, this technology has the potential to save lives and provide crucial support during times of crisis.
A quad-rotor drone is a complex machine that requires several key parts and equipment to function effectively as a wireless energy transmitter. These parts include:
Batteries: The quadrotor drone requires a reliable and powerful battery to provide energy to its systems. Different types of batteries can be used, including Li-Po, Li-Ion, and NiMH batteries, each with its own unique properties and benefits.
Motors: The motors are responsible for generating the rotational force required to propel the drone forward. The choice of motors will depend on the power and energy requirements of the drone, as well as its weight and size.
Rotors: The rotors are the key components that provide lift and propulsion to the drone. In a quad rotor drone, there are four rotors, each with its own motor, that are positioned at 90-degree angles to each other. The closed-form toroidal propeller, consisting of two blades looping together, is used in some designs to reduce drag and increase stiffness.
Sensors: To ensure a stable flight and automated navigation, a variety of sensors are used on quad-rotor drones. These sensors include accelerometers, gyroscopes, magnetometers, and barometers, which provide information on the drone's orientation, speed, and altitude. In addition, cameras and other imaging sensors may be used for navigation and obstacle avoidance.
By using these components in a carefully designed and optimized system, the quadrotor drone can be transformed into a powerful and versatile tool for wireless energy transmission. Whether providing power to communities during times of crisis or flying out to areas that need immediate energy, the quad-rotor drone has the potential to revolutionize the way we transmit and access energy.
To enable the quad-rotor drone to fly autonomously and navigate through the environment, it is crucial to equip the drone with cameras and imaging sensors. These sensors play a critical role in ensuring the safety and stability of the drone during flight. The specific types of cameras and imaging sensors used for navigation and obstacle avoidance may vary depending on the design of the drone and the specific requirements of the task at hand.
One common type of camera used in drone navigation is a visual navigation camera. This camera is typically positioned on the front of the drone and captures images of the environment that are then processed to determine the drone's position and velocity. The visual navigation camera is crucial for navigation and obstacle avoidance, as it enables the drone to identify obstacles in its path and plan a safe flight trajectory.
Another type of imaging sensor that is often used in drone navigation is a LIDAR (Light Detection and Ranging) sensor. This sensor uses lasers to measure distances to nearby objects and creates a 3D map of the environment that the drone can use to navigate. LIDAR sensors are particularly useful in challenging environments, such as dense forests or urban canyons, where other types of navigation sensors may be less effective.
In addition to these sensors, many quad rotor drones also use ultrasonic sensors and infrared sensors for navigation and obstacle avoidance. Ultrasonic sensors emit sound waves that bounce off of objects in the environment, and the drone can then use the time delay between the emission and reception of the sound waves to determine the distance to nearby objects. Infrared sensors work similarly, but use infrared light instead of sound waves. These sensors can detect objects and obstacles that are not visible to the visual navigation camera, such as obstacles that are obscured by dust or fog.
Overall, the combination of cameras and imaging sensors on the quadrotor drone plays a crucial role in enabling the drone to navigate and avoid obstacles, ensuring that it can safely and efficiently transmit energy wirelessly.
The quad-rotor drone used as a wireless energy transmitter requires a number of key components to function effectively. These components include:
Propellers: The propellers are responsible for providing the lift and propulsion necessary for the drone to fly. In the case of this wireless energy transmitter, a closed-form toroidal propeller is utilized due to its advantages in reducing drag and increasing stiffness.
Motors: The motors are responsible for driving the propellers. The type of motor used will depend on the size and weight of the drone, as well as the desired performance capabilities. Brushless DC motors are a popular choice for quad-rotor drones as they provide a high level of efficiency and reliability.
Electronic Speed Controllers (ESCs): The ESCs are responsible for controlling the speed of the motors. They receive signals from the flight controller and adjust the motor speed accordingly.
Flight Controller: The flight controller is the central processing unit of the drone and is responsible for controlling all of the drone’s systems. It receives inputs from the various sensors and cameras and processes this information to determine the appropriate control signals to send to the motors and other systems.
Battery: The battery provides the power necessary for the drone to fly and transmit energy wirelessly. The type of battery used will depend on the energy requirements of the drone and the desired flight time. Lithium Polymer (LiPo) batteries are a popular choice due to their high energy density and lightweight.
Sensors and Cameras: The sensors and cameras used in the quad rotor drone include various types of imaging sensors, such as RGB cameras, thermal cameras, and LIDAR sensors, for navigation and obstacle avoidance. These sensors and cameras are essential for ensuring the safe and effective operation of the drone.
Wireless Energy Transmission System: The wireless energy transmission system is responsible for transmitting energy wirelessly from the drone to the desired location. This system typically includes a transmitter and receiver, as well as other components to ensure efficient and reliable energy transmission.
These components work together to create a functional and capable quad-rotor drone that can be used as a wireless energy transmitter.
A wireless energy transmission system requires specialized equipment to ensure the efficient and safe transfer of energy from the source to the target. One of the key components in this system is the rectenna, which is a combination of a rectifying antenna and a diode rectifier circuit. It is responsible for converting the incoming radio frequency (RF) energy into direct current (DC) electrical energy, which can then be stored and used by the target device.
Another important component of the wireless energy transmission system is the 2-D material molybdenum disulfide (MoS2). This material has unique electronic properties that make it ideal for use in wireless energy transmission systems. It has high electrical conductivity and thermal stability, which helps to increase the efficiency of energy transfer. Additionally, MoS2 is lightweight and flexible, making it suitable for use in portable and wearable wireless energy transmission systems.
In conclusion, the use of specialized equipment such as rectennas and MoS2 is crucial for the successful implementation of a wireless energy transmission system using quad-rotor drones. These components help to ensure the safe and efficient transfer of energy, while also providing the necessary features and characteristics required for the successful operation of such a system.
The rectenna is a critical component of a wireless energy transmission system. It is responsible for converting the radio frequency (RF) signals that are transmitted from the power source into usable electrical energy. This conversion process is achieved through the rectification of the RF signals, which involves rectifying the AC signal into a DC signal that can be used to power electronic devices.
The rectenna is essentially made up of two components: an antenna and a rectifier circuit. The antenna is responsible for receiving the RF signals from the power source and transmitting them to the rectifier circuit. The rectifier circuit is then responsible for converting the RF signals into usable electrical energy.
The rectifier circuit of a rectenna typically uses a diode or a set of diodes to rectify the AC signal. The diode acts as a one-way valve for electrical current, allowing the current to flow in one direction only. This means that it allows the positive half-cycles of the AC signal to pass through while blocking the negative half-cycles. The result is a DC signal that can be used to power electronic devices.
In addition to diodes, rectennas may also use more advanced rectification technologies such as Schottky diodes or high electron mobility transistors (HEMTs). These technologies are more efficient and have faster switching speeds, allowing for greater rectification performance.
In summary, the rectenna plays a vital role in a wireless energy transmission system by converting the RF signals into usable electrical energy. Its design and components are critical to ensuring that the system operates effectively and efficiently.
The software and algorithms play a crucial role in the functioning of the quadrotor drone as a wireless energy transmitter. The software must be able to control and stabilize the drone in flight, navigate and avoid obstacles, communicate with other devices, and control the wireless energy transmission process.
For flight control, the drone must have a control algorithm that can respond to inputs from various sensors such as the accelerometer, gyroscope, and barometer. This algorithm must also be able to make decisions based on the data received from these sensors to maintain stability and control the flight path of the drone.
For navigation, the drone must have an obstacle avoidance algorithm that can detect and avoid obstacles using data from imaging sensors such as cameras and LIDAR. The drone must also have a navigation algorithm that can calculate the optimal flight path based on the data received from these sensors.
For wireless energy transmission, the drone must have an energy transmission algorithm that can regulate the transmission of energy to ensure that the energy received by the rectenna is within safe levels. The drone must also have a communication algorithm that can communicate with other devices such as the energy receiver to ensure that the energy transmission process is functioning correctly.
In addition, the software must be able to store and process large amounts of data, making it necessary for the drone to have a high-performance processor and sufficient memory. The software must also be programmed to operate in real time, making it necessary for the drone to have a real-time operating system.
Overall, the software and algorithms are essential components of the quadrotor drone's functionality as a wireless energy transmitter, as they allow the drone to control flight, navigate and avoid obstacles, and transmit energy wirelessly.
The code for flight control, navigation, and energy transmission is a critical component of the quad-rotor drone system. The flight control code is responsible for maintaining the stability of the drone and ensuring it remains in its desired position in the air. This is achieved through a combination of algorithms that take into account the inputs from various sensors, including the accelerometer, gyroscope, and barometer. The navigation code uses data from these sensors and additional imaging sensors such as cameras and LIDAR to determine the drone's position in the air and navigate it through the environment.
The energy transmission code is responsible for managing the transmission of electrical energy from the drone to a receiving antenna, known as a rectenna. This code must ensure that the energy is transmitted efficiently and effectively, while also monitoring the battery levels of the drone to prevent it from running out of power during transmission. The energy transmission code is also responsible for ensuring the safety of the transmission and preventing the transmission of harmful radio frequency signals.
Examples of the code used for flight control, navigation, and energy transmission include the use of PID (proportional-integral-derivative) algorithms to control the drone's movements and maintain stability. For navigation, the code might use a SLAM (simultaneous localization and mapping) algorithm to create a map of the environment and determine the drone's location within that map. For energy transmission, the code might include algorithms to optimize the transmission frequency and power levels, as well as safety protocols to prevent harmful transmissions.
In summary, the code for flight control, navigation, and energy transmission is a complex and critical component of the quad rotor drone system. It combines algorithms and mathematical models to ensure that the drone functions as intended and achieves its goals of stable flight, efficient navigation, and effective energy transmission
.The algorithm that controls the rotors of the quadrotor drone is a crucial component in ensuring safe and efficient flight. This algorithm is responsible for calculating the drone's position and orientation based on information from GPS sensors and other environmental factors, such as altitude, wind speed and direction, and temperature. The algorithm then uses this information to make adjustments to the rotors, allowing the drone to maintain a stable flight and fly to its desired location.
One key aspect of the flight control algorithm is the use of GPS information. The GPS sensors on the drone provide data on the drone's current position, speed, and direction of movement. This information is used to calculate the drone's desired path, taking into account the desired speed and altitude. The algorithm then uses this data to determine the required rotation speed and direction of each rotor to maintain the drone's position and altitude.
In addition to GPS information, the flight control algorithm also takes into account other environmental factors, such as wind speed and direction. These factors can affect the drone's flight, so the algorithm must adjust the rotors accordingly to maintain stability. For example, if the wind is blowing from one direction, the algorithm may need to adjust the rotors' speed and direction to counterbalance the wind's effects.
Finally, the flight control algorithm must also consider the drone's proximity to the ground. This is especially important when flying at low altitudes, where the drone is more likely to encounter obstacles. To prevent collisions, the algorithm uses data from cameras and other imaging sensors to detect obstacles in the drone's path and adjust its flight accordingly.
Overall, the flight control algorithm is a complex system that integrates data from various sources to control the rotors and maintain a stable flight for the quad rotor drone. This is essential for ensuring safe and efficient wireless energy transmission.
The code that allows the drone to pick up on the electricity of other Bluetooth wireless networks and transmit that energy back to the house involves several steps. Firstly, the drone must be equipped with a Bluetooth receiver and a power amplifier circuit that can capture the radio frequency signals. These signals are then processed through the rectenna, which converts them into usable electrical energy.
The code that controls this process involves algorithms that constantly monitor the strength of the incoming Bluetooth signals and adjust the power amplification circuit accordingly. Additionally, the code must ensure that the energy transmitted back to the house is done so in a way that does not interfere with other wireless networks or cause harm to other electronic devices.
An example of this code might involve a line that checks the incoming Bluetooth signal strength and adjusts the power amplification circuit accordingly:
scss
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if (bluetoothSignalStrength > threshold) {
powerAmplificationCircuit.increasePower();
} else {
powerAmplificationCircuit.decreasePower();
}
Similarly, the code must also ensure that the energy transmitted back to the house is within safe limits and does not cause harm to other electronic devices:
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if (transmittedEnergy > maxSafeEnergy) {
transmittedEnergy = maxSafeEnergy;
}
Python for Battery Management Code Example —
import time
# Battery management class
class BatteryManagement:
def __init__(self, drone, threshold=0.2):
self.drone = drone
self.threshold = threshold
self.battery_level = None
self.estimated_time = None
# Function to check the battery level
def check_battery_level(self):
self.battery_level = self.drone.get_battery_level()
print(“Current battery level:”, self.battery_level)
return self.battery_level
# Function to estimate remaining flight time
def estimate_remaining_time(self):
self.estimated_time = self.drone.get_estimated_flight_time()
print(“Estimated remaining flight time:”, self.estimated_time)
return self.estimated_time
# Function to issue commands to the drone
def issue_command(self):
if self.battery_level <= self.threshold:
print(“Battery level low. Returning to charging station…”)
self.drone.return_to_base()
else:
print(“Battery level sufficient. Continuing flight…”)
# Example usage
drone = Drone()
battery_manager = BatteryManagement(drone)
while True:
current_level = battery_manager.check_battery_level()
remaining_time = battery_manager.estimate_remaining_time()
battery_manager.issue_command()
time.sleep(60) # check battery level every minute
or
import time
# Battery management class
class BatteryManagement:
def __init__(self, max_capacity, warning_threshold):
self.max_capacity = max_capacity
self.warning_threshold = warning_threshold
self.current_level = max_capacity
def get_remaining_percentage(self):
return (self.current_level / self.max_capacity) * 100
def get_remaining_time(self):
# Assume a constant power consumption rate
power_consumption = 10 # watts
return (self.current_level / power_consumption) * 3600
def update_battery_level(self, level):
self.current_level = level
if self.get_remaining_percentage() < self.warning_threshold:
# Issue warning
print(“Battery level low. Returning to charging station.”)
# Return to charging station or land
return “low_battery”
else:
return “normal”
# Example usage
bm = BatteryManagement(10000, 10) # 10 Ah battery, warning threshold of 10%
while True:
# Simulate battery usage
bm.update_battery_level(bm.current_level — 50)
print(“Remaining battery:”, bm.get_remaining_percentage(), “%”)
print(“Estimated remaining flight time:”, bm.get_remaining_time(), “seconds”)
time.sleep(1)
This code demonstrates a basic implementation of a battery management algorithm for a drone using Python. The BatteryManagement class is initialized with the drone object and a threshold value for the minimum battery level at which the drone should return to the charging station. The check_battery_level function retrieves the current battery level from the drone and stores it in the battery_level attribute. The estimate_remaining_time function estimates the remaining flight time based on the current battery level and stores it in the estimated_time attribute. The issue_command function then checks if the battery level is below the threshold value. If it is, it issues a command to the drone to return to the charging station. If the battery level is above the threshold, it continues the flight. The example usage shows how these functions can be used in a loop to continuously monitor and manage the battery level of the drone.
import time
# Define minimum battery level for safe flight
min_battery_level = 20
# Define charging station location coordinates
charging_station_lat = 37.788022
charging_station_long = -122.399797
# Define current battery level and flight time variables
battery_level = 100
flight_time = 0
while True:
# Check current battery level
battery_level = checkBatteryLevel()
if battery_level <= min_battery_level:
# Issue command for drone to return to charging station
returnToChargingStation()
else:
# Estimate remaining flight time based on current battery level
flight_time = estimateRemainingFlightTime(battery_level)
# Check if drone is within range of a wireless network
wireless_network = checkWirelessNetwork()
if wireless_network:
# Attempt to connect to wireless network
connectToWirelessNetwork(wireless_network)
# Attempt to transmit energy back to the house
transmitEnergy()
# Sleep for a short period before checking battery level again
time.sleep(60)
def checkBatteryLevel():
# Code to check current battery level of drone
return current_battery_level
def returnToChargingStation():
# Code to navigate drone to charging station location
pass
def estimateRemainingFlightTime(battery_level):
# Code to estimate remaining flight time based on current battery level
pass
def checkWirelessNetwork():
# Code to scan for nearby wireless networks
return wireless_network
def connectToWirelessNetwork(network):
# Code to connect to a wireless network
pass
def transmitEnergy():
# Code to transmit energy back to the house
pass
or import bluetooth
# Bluetooth device address of wireless power source
BT_DEVICE_ADDRESS = “00:11:22:33:44:55”
# Connect to wireless power source
power_source = bluetooth.BluetoothSocket(bluetooth.RFCOMM)
power_source.connect((BT_DEVICE_ADDRESS, 1))
# Get current wireless power level
power_level = power_source.recv(1024)
# Transmit power back to house
drone.transmit_power(power_level)
# Close connection to wireless power source
power_source.close()
This code uses a while loop to continuously check the drone’s battery level. If the battery level falls below a defined minimum level, the drone is instructed to return to a charging station. If the battery level is sufficient, the code estimates the remaining flight time and check for nearby wireless networks. If a wireless network is found, it will try to connect to it and transmit energy back to the house. The specific implementation of the functions used in the example above, such as checkBatteryLevel, returnToChargingStation, estimateRemainingFlightTime, checkWirelessNetwork, connectToWirelessNetwork, and transmitEnergy will depend on the specific drone hardware and software being used.
The script starts by importing the numpy library, which is a library for working with arrays in Python. Next, the script defines the frequency of the incoming RF signal, which is 2.4 GHz in this case. The script then defines the dimensions of the antenna array, which is 0.5 meters by 0.5 meters in this case.
The script then calculates the wavelength of the incoming signal by dividing the speed of light (3 x 10⁸ m/s) by the frequency of the signal. This is used to determine the spacing of the antenna elements.
The script then creates an array of zeros with the same dimensions as the antenna array and assigns the phase shift to each element of the array. This is done by using a nested for loop, where the outer loop iterates through the rows of the array and the inner loop iterates through the columns of the array.
The script then defines the incoming RF signal as a sine wave and performs the antenna array multiplication by multiply the RF signal with the antenna array. This results in a received signal.
Finally, the script performs the RF to DC conversion by summing up all the elements of the received signal, resulting in the DC signal.
import GPS
import ultrasonic_sensor
# Set the minimum safe distance from the ground in meters
min_safe_distance = 2
while True:
# Get the current GPS coordinates of the drone
current_coordinates = GPS.get_coordinates()
# Get the distance from the ground using the ultrasonic sensor
distance_from_ground = ultrasonic_sensor.get_distance()
# If the distance from the ground is less than the minimum safe distance, issue a command to move up
if distance_from_ground < min_safe_distance:
drone.move_up()
# Else, if the distance from the ground is greater than the minimum safe distance, issue a command to maintain altitude
else:
drone.maintain_altitude()
This code uses the GPS module to get the current coordinates of the drone and the ultrasonic sensor module to get the distance from the ground. A minimum safe distance is set and the code enters into a loop where it continuously checks the distance from the ground. If the distance is less than the minimum safe distance, it issues a command to move up, if not it maintains its altitude. The ultrasonic sensor is commonly used to measure the distance, it emits an ultrasonic sound wave which travels through the air, bounces off an object and returns back to the sensor. By measuring the time it takes for the sound wave to return, the sensor can calculate the distance to the object.
Please note:
dronein the above code is an object or instance of a drone class that should have methods to control the drone's movements- The code is a simplified version of the drone’s operation and more details like adding limits, checks for errors, etc are needed for the actual implementation.
import GPS
import sensor
def drone_flight_control():
# Get current GPS coordinates
current_coordinates = GPS.get_coordinates()
# Get distance from ground using sensor data
distance_from_ground = sensor.get_distance()
# Check if distance from ground is safe
if distance_from_ground < SAFE_DISTANCE:
# Issue command to drone to ascend
drone.ascend()
elif distance_from_ground > SAFE_DISTANCE:
# Issue command to drone to descend
drone.descend()
else:
# Maintain current altitude
pass
# Check if drone is within safe proximity of any objects
if sensor.detect_obstacles(current_coordinates):
# Issue command to drone to move away from obstacle
drone.move_away()
else:
# Continue with normal flight
pass
This code snippet is an example of how the drone’s automated system based on distance from the ground and GPS could be implemented. It uses the GPS module to get the drone’s current coordinates, and a sensor module to get the distance from the ground. The code checks if the distance is less than a predefined safe distance, and if it is, it issues a command to the drone to ascend. If the distance is greater than the safe distance, it issues a command to the drone to descend. If the distance is exactly equal to the safe distance, it does nothing. This allows the drone to maintain a safe distance from the ground at all times. Additionally, the code checks for obstacles in the drone’s current location using the sensor module and if it detects any, it issues a command to the drone to move away from the obstacle.
import numpy as np
# Define the frequency of the incoming RF signal
frequency = 2.4e9
# Define the antenna array dimensions
antenna_length = 0.5 # meters
antenna_width = 0.5 # meters
# Calculate the wavelength of the incoming signal
wavelength = 3e8/frequency
# Create an array of antenna elements
antenna_array = np.zeros((antenna_length, antenna_width))
# Define the antenna element spacing
element_spacing = wavelength/2
# Loop through each element in the antenna array
for i in range(antenna_length):
for j in range(antenna_width):
# Calculate the phase shift for each element
phase_shift = 2*np.pi*(i*element_spacing + j*element_spacing)/wavelength
# Assign the phase shift to the current element
antenna_array[i][j] = phase_shift
# Define the incoming RF signal
rf_signal = np.sin(2*np.pi*frequency*t)
# Perform the antenna array multiplication
received_signal = np.multiply(rf_signal, antenna_array)
# Perform the RF to DC conversion
dc_signal = np.sum(received_signal)
This code defines an antenna array with a given length and width, with elements spaced a certain distance apart. It then calculates the phase shift for each element based on its position within the array. The incoming RF signal is defined and multiplied with the antenna array, resulting in a received signal. Finally, the received signal is converted to a DC signal by summing all of its values.
It’s important to note that this is a simplified example of code that would be used in a rectenna algorithm, and that in practice, there would likely be more complex calculations and considerations such as noise, interference and other factors that affect the efficiency of the rectenna. Also, in order to operate the drone with this code, the drone should have a rectenna, a device that can convert RF energy into DC energy.
import time
# Initialize battery level variable
battery_level = 100
# Define function to check battery level
def check_battery():
global battery_level
return battery_level
# Define function to estimate remaining flight time
def estimate_flight_time():
global battery_level
if battery_level > 75:
return “More than 15 minutes”
elif battery_level > 50:
return “Between 10 and 15 minutes”
elif battery_level > 25:
return “Between 5 and 10 minutes”
else:
return “Less than 5 minutes”
# Define function to issue commands to return to charging station or land
def battery_warning():
global battery_level
if battery_level < 20:
print(“Returning to charging station”)
elif battery_level < 10:
print(“Battery levels critical. Landing now.”)
# Main loop
while True:
battery_level = check_battery()
print(“Battery level: “ + str(battery_level) + “%”)
print(“Estimated flight time remaining: “ + estimate_flight_time())
battery_warning()
time.sleep(60) # check battery level every 60 seconds
Regarding the code for the rectenna and converting RF energy into DC energy, it’s a bit more complex and beyond the scope of this platform. However, the rectenna code would involve designing and implementing a rectifying circuit that can convert the RF energy into DC energy. It would also involve calculations and considerations such as noise, interference, and antenna design. The code for the conversion would involve designing and implementing a circuit that can convert the DC energy into a usable form for the system.
Also, for the automated system based on distance from the ground and GPS, the code would involve implementing algorithms for determining the drone’s distance from the ground and other objects using sensor data, such as data from a sonar sensor or lidar sensor, as well as GPS data. The algorithm would also need to take into account the drone’s current velocity and trajectory in order to make safe and accurate distance calculations. The code would also involve implementing a control system that can adjust the drone’s altitude and position in real time based on the distance calculations, in order to maintain a safe distance from the ground and other objects.
import VR_AR_headset_library
def interpret_headset_commands(headset_data):
“””
Interpret commands from the VR/AR headset and translate them into drone commands
“””
roll = headset_data[‘roll’]
pitch = headset_data[‘pitch’]
yaw = headset_data[‘yaw’]
thrust = headset_data[‘thrust’]
return (roll, pitch, yaw, thrust)
def flight_control_algorithm(drone_state, command):
“””
Algorithm for controlling the drone’s flight based on commands from the VR/AR headset
“””
roll, pitch, yaw, thrust = command
drone_state.roll = roll
drone_state.pitch = pitch
drone_state.yaw = yaw
drone_state.thrust = thrust
drone_state.update_state()
# Example usage
headset = VR_AR_headset_library.connect()
drone = Drone()
while True:
headset_data = headset.get_data()
command = interpret_headset_commands(headset_data)
flight_control_algorithm(drone, command)
This code imports a library for connecting to the VR/AR headset and uses it to get data from the headset in real-time. The interpret_headset_commands function takes the headset data as input and translates it into roll, pitch, yaw, and thrust commands for the drone. The flight_control_algorithm function then uses these commands to update the drone's state. The code also has an example of usage of the function and classes defined, where a connection to the headset is established and the data is being gathered on a continuous loop, and sending commands to the drone. It is important to note that this is a simplified example, and a real-world implementation would likely involve additional safety checks and error handling. Also, this code doesn't handle the calculations and considerations such as noise, and interference.
In summary, the code for wireless energy transmission using quadrotor drones is a complex system that involves monitoring and adjusting the Bluetooth signal strength, processing the signals through the rectenna, and ensuring that the energy transmitted back to the house is done so in a safe and non-interfering manner.
Having the toroidal propeller, a new design that allows drones to operate more quietly by minimizing the drag effects of swirling air tunnels at the tips of the blades and strengthening the overall stiffness of the propeller. This closed-form structure reduces the propeller’s acoustic signature, making it less of an annoyance to humans. Prototype tests have shown that the toroidal propeller can achieve thrust levels comparable to conventional propellers at similar power levels, and allow drones to operate at a distance that is twice as far as typical operation without taxing human hearing. This design may accelerate the acceptance of drones for a wide range of uses such as aerial deliveries, cinematography, industrial or infrastructure inspections, and agricultural monitoring.
The use of multiple drones in a network to transmit energy and data wirelessly offers several benefits. By deploying multiple drones, the system can provide wider coverage and better reliability compared to a single drone. This means that multiple devices can be powered at the same time and there is a lower chance of interruption in energy transmission.
Additionally, having multiple drones in a network enables the system to be more resilient against failures and to continue functioning even if one of the drones encounters technical difficulties. This can be particularly important in remote areas or in times of crisis where the ability to continuously power critical devices can be critical.
Moreover, having multiple drones can also allows energy transmission to be optimized and controlled more effectively. For example, the energy transmission can be balanced among the drones to ensure that each drone is handling an equal amount of energy. This can increase the efficiency and lifespan of the drones and prolong the time between maintenance and replacements.
Overall, the use of multiple drones in a network to transmit energy and data wirelessly offers greater flexibility, reliability, and scalability compared to a single drone solution. This makes it an attractive solution for a wide range of applications and environments, from powering individual homes to powering entire communities during times of crisis.
The central wireless power plant or capacitor, often mounted on a transport vehicle such as an 18-wheeler truck, serves as the hub of the network for wireless energy transmission. In this scenario, multiple quad-rotor drones serve as "tentacles" that can be deployed to specific locations to transmit energy wirelessly. This system provides a number of benefits, including increased flexibility and mobility, as well as the ability to quickly respond to changing energy demands in real time.
The central power plant or capacitor is equipped with high-energy storage capacitors and generators to generate and store energy. The energy generated by the central power plant is then transmitted wirelessly to the quad rotor drones via radio frequency signals. The drones are equipped with rectennas to convert the radio frequency signals into usable electrical energy, which is then transmitted to the end user.
In this networked system, each drone can be individually controlled and optimized for specific energy transmission tasks. This allows for improved energy efficiency and the ability to adapt to changing energy demands. Furthermore, the use of multiple drones in a network provides increased resilience, as the system can continue to operate even if one or more drones fail.
In addition to transmitting energy, the quad-rotor drones can also be used for data transmissions, such as GPS coordinates and environmental data. This data can be used to optimize the energy transmission process, further increasing the efficiency of the system.
In conclusion, the central wireless power plant or capacitor and multiple quadrotor drone "tentacles" form a highly flexible and efficient wireless energy transmission system that can respond to changing energy demands in real-time, while providing increased resilience and adaptability.
The flexibility and adaptability of the wireless energy transmission system using quad rotor drones is one of its key advantages. This system can be tailored to meet the unique energy needs of different communities and environments, ensuring that energy is delivered where it is most needed.
For example, in rural communities, the system could be configured to provide energy to remote areas that are not connected to traditional electrical grids. In urban areas, the system could be configured to provide a backup source of energy during power outages or to supplement the existing electrical grid during times of high demand.
Another key advantage of the system is its ability to quickly respond to changes in energy demand. In times of crisis, such as natural disasters, the system could be quickly deployed to provide energy to affected areas. The use of multiple drones in a network also allows for energy to be transmitted to multiple locations simultaneously, providing a more comprehensive solution to energy needs.
In addition, the system can be configured to meet the specific energy needs of different communities and environments, such as the use of different battery types or the incorporation of alternative energy sources, such as solar panels. This makes the system a highly adaptable solution for a variety of energy needs.
The wireless energy transmission system using quadrotor drones is a cutting-edge technology that offers numerous benefits over traditional energy transmission methods. This system is designed to help communities access to power in remote locations, during crisis situations, or when traditional power grids are down. The quadrotor drone itself is a sophisticated piece of technology, featuring a closed-form toroidal propeller, which reduces drag and increases stiffness, providing increased stability and efficiency in flight. Additionally, the drone is equipped with a range of sensors and cameras to assist with navigation, obstacle avoidance, and flight control.
One of the key components of the wireless energy transmission system is the rectenna, which converts radio frequency signals into usable electrical energy. This device is paired with a 2-D material molybdenum disulfide (MoS2) to increase its efficiency. The quad rotor drone operates through a combination of software and algorithms, with code for flight control, navigation, and energy transmission. The drone is equipped with GPS and algorithms that control the rotors based on its location, distance from the ground, and other environmental factors.
The system is highly flexible and adaptable, able to meet the needs of different communities and environments. By using multiple drones in a network, energy and data can be transmitted wirelessly, increasing its range and efficiency. The central wireless power plant, or capacitor, serves as the hub of the network, with the drones acting as "tentacles" transmitting energy to specific locations.
In conclusion, the wireless energy transmission system using quad-rotor drones is a revolutionary technology that offers a wide range of benefits, including increased efficiency, flexibility, and adaptability. With the potential to help communities access to power in remote locations, provide a backup power source during crisis situations, and improve overall energy transmission, this technology has the potential to revolutionize the energy industry and help improve the lives of people all over the world.
The wireless energy transmission system using quad rotor drones is a novel approach to providing power to communities and homes that promises to revolutionize the power industry. The system is designed to use quad rotor drones equipped with specialized equipment, including rectennas and 2-D material molybdenum disulfide (MoS2), to transmit electrical energy wirelessly from a central hub to various locations. This innovative technology has several key benefits that make it a promising solution for the power industry.
One of the key benefits of the wireless energy transmission system is its flexibility and adaptability. The system is designed to be highly flexible and adaptable, allowing it to be customized to meet the needs of different communities and environments. This means that the system can be configured to meet the specific requirements of a particular community or environment, providing a highly efficient and effective solution for the provision of power.
Another key benefit of the system is its ability to transmit energy wirelessly over large distances. The system uses quad-rotor drones to transmit electrical energy from a central hub to specific locations, enabling it to reach remote or hard-to-reach areas that are difficult to access with traditional power grids. This makes it a valuable solution for providing power to communities in rural or remote areas, where traditional power grids are either unavailable or unreliable.
In addition to its flexibility and adaptability, the wireless energy transmission system is also highly efficient. The system uses specialized equipment, including rectennas and 2-D material molybdenum disulfide (MoS2), to convert radio frequency signals into usable electrical energy, which can be transmitted wirelessly to specific locations. The system also uses algorithms to control the rotors based on GPS location and distance from the ground, allowing it to fly autonomously and transmit energy more efficiently.
Finally, the wireless energy transmission system is a scalable and cost-effective solution for the provision of power. The system can be configured to meet the needs of different communities and environments, and its use of quad rotor drones to transmit energy eliminates the need for traditional power grids, reducing the costs associated with their construction and maintenance.
In conclusion, the wireless energy transmission system using quad rotor drones is a promising solution for the power industry that offers several key benefits, including flexibility, adaptability, efficiency, and cost-effectiveness. This innovative technology has the potential to revolutionize the provision of power to communities and homes, providing a highly efficient and effective solution for the power industry.
The use of a wireless energy transmission system using quad-rotor drones provides numerous sustainability benefits. Firstly, it allows for the harnessing and utilization of wasted energy from radio frequency (RF) sources, such as Bluetooth and Wi-Fi networks. This reduces the amount of energy being wasted and helps to conserve resources.
Secondly, the system reduces dependence on fossil fuels, which are a finite and non-renewable source of energy. Fossil fuels also contribute to greenhouse gas emissions, which are a major contributor to climate change. By using a wireless energy transmission system, communities, and homes can reduce their carbon footprint and contribute to a cleaner and more sustainable energy system.
Additionally, the use of quad-rotor drones allows for the energy transmission system to be highly adaptable and flexible. Different communities and environments have unique energy needs, and the system can be tailored to meet these specific requirements. For example, rural communities may need a larger energy transmission system, whereas urban communities may require a more compact and efficient system. The use of quad-rotor drones allows for the system to be easily scaled and modified to meet the needs of different communities.
In conclusion, the wireless energy transmission system using quad-rotor drones offers numerous sustainability benefits, including the harnessing of wasted energy, reducing dependence on fossil fuels, and being highly adaptable to meet the needs of different communities and environments. This system has the potential to revolutionize the provision of power to communities and homes, providing a clean, sustainable, and efficient solution to meet their energy needs.
The outlook for the future of the wireless energy transmission system using quad-rotor drones is bright and holds great potential for changing the way energy is delivered to homes, communities, and other devices. With advancements in drone technology and the integration of new materials, such as 2-D molybdenum disulfide (MoS2), the capabilities of this system are likely to expand and improve over time.
The versatility of the system makes it a potential solution for many different communities and environments. By using wasted energy from RF sources, it has the potential to greatly reduce dependence on fossil fuels and provide a more sustainable source of power.
The future of this technology could see its integration into cities, where multiple drones could work together in a network to provide energy to homes and businesses, reducing the need for traditional power plants and power lines. It could also potentially be used in disaster relief efforts, providing quick and efficient energy to affected areas without the need for repair and installation of traditional power systems.
In addition, the system could be integrated into other devices, such as laptops, cell phones, and even vehicles, allowing them to be powered wirelessly without the need for traditional power sources.
Overall, the wireless energy transmission system using quad-rotor drones holds a great deal of promise for revolutionizing the way we think about energy and power delivery. With its ability to be adapted to meet the needs of different communities and environments, its potential for reducing dependence on fossil fuels, and its many other benefits, it is a technology to watch in the coming years.
In conclusion, the wireless energy transmission system using quad-rotor drones is a revolutionary technology that has the potential to greatly benefit communities and individuals by providing a more efficient and sustainable way of accessing power. The system is comprised of several key parts, including specialized equipment for wireless energy transmission, flight control algorithms, and battery and rotor components. The closed-form toroidal propellers reduce drag and increase stiffness, while a variety of sensors and cameras are used for automated navigation and flight control. Additionally, the system is highly flexible and adaptable, making it suitable for a wide range of communities and environments. In military applications, the use of wireless energy transmission drones could provide a way to power equipment and supplies in remote or difficult-to-access locations. By eliminating the need for traditional power sources, drones could allow for greater operational independence and versatility. However, the potential military applications of this technology also raise concerns around the ethical implications of using drones for energy transmission.
By harnessing wasted energy from RF sources and reducing dependence on fossil fuels, this technology has significant sustainability benefits. The future outlook for the technology is promising, with potential for future developments and applications in a variety of settings, including cities and peacetime scenarios. Overall, the wireless energy transmission system using quadrotor drones represents a major step forward in the provision of power to communities and homes and has the potential to greatly improve energy access and efficiency for individuals across the world.
thank you for reading what me and Chat GPT and I wrote.
Citation.
https://news.mit.edu/2019/converting-wi-fi-signals-electricity-0128
Further Python code for controls the rotors’ speed and direction, as well as code for maintaining the drone’s altitude and orientation.
import time
Define the desired altitude in meters
desired_altitude = 10
Define the current altitude and orientation variables
current_altitude = 0 current_orientation = 0
Define the PID controllers for altitude and orientation
altitude_pid = PID(kp=0.5, ki=0.01, kd=0.01) orientation_pid = PID(kp=0.5, ki=0.01, kd=0.01)
while True: # Read the current altitude and orientation from the sensors current_altitude = readAltitudeSensor() current_orientation = readOrientationSensor()
makefileCopy code# Calculate the error for the altitude and orientation PID controllers
altitude_error = desired_altitude - current_altitude
orientation_error = 0 - current_orientation# Calculate the new rotor speeds using the PID controllers
rotor_speed1 = altitude_pid.update(altitude_error) + orientation_pid.update(orientation_error)
rotor_speed2 = altitude_pid.update(altitude_error) - orientation_pid.update(orientation_error)
rotor_speed3 = altitude_pid.update(altitude_error) + orientation_pid.update(orientation_error)
rotor_speed4 = altitude_pid.update(altitude_error) - orientation_pid.update(orientation_error)# Set the rotor speeds
setRotorSpeed(rotor_speed1, rotor_speed2, rotor_speed3, rotor_speed4)# Sleep for a short period before reading sensor data again
time.sleep(0.1)def readAltitudeSensor(): # Code to read altitude from sensor return current_altitude
def readOrientationSensor(): # Code to read orientation from sensor return current_orientation
def setRotorSpeed(rotor_speed1, rotor_speed2, rotor_speed3, rotor_speed4): # Code to set the rotor speeds pass
class PID: def init(self, kp, ki, kd): self.kp = kp self.ki = ki self.kd = kd self.previous_error = 0 self.integral = 0
luaCopy codedef update(self, error):
self.integral += error
derivative = error - self.previous_error
output = self.kp * error + self.ki * self.integral + self.kd * derivative
self.previous_error = error
return outputdef correct_orientation(current_orientation, desired_orientation): # Get the difference between the current and desired orientations delta_orientation = desired_orientation — current_orientation # Check if the difference is greater than 180 degrees if delta_orientation > 180: # Subtract 360 degrees from the difference delta_orientation -= 360 elif delta_orientation < -180: # Add 360 degrees to the difference delta_orientation += 360 # Set the rotation speed of the drone based on the difference rotation_speed = delta_orientation * ORIENTATION_PID_CONSTANT # Set
import motor_controller
Define the maximum rotor speed
max_rotor_speed = 1000
Define the minimum rotor speed
min_rotor_speed = 0
Define the current rotor speed
current_rotor_speed = 0
Define the desired rotor speed
desired_rotor_speed = 0
Define the rotor direction (1 for clockwise, -1 for counterclockwise)
rotor_direction = 1
Define the target altitude
target_altitude = 2
Define the current altitude
current_altitude = 0
Define the altitude tolerance
altitude_tolerance = 0.1
def setRotorSpeed(speed): # Set the current rotor speed to the desired speed current_rotor_speed = speed # Pass the current rotor speed to the motor controller motor_controller.setSpeed(current_rotor_speed)
def setRotorDirection(direction): # Set the rotor direction rotor_direction = direction # Pass the rotor direction to the motor controller motor_controller.setDirection(rotor_direction)
def maintainAltitude(): # Get the current altitude from the sensor current_altitude = sensor.getAltitude() # Check if the current altitude is within the tolerance of the target altitude if abs(current_altitude — target_altitude) > altitude_tolerance: # Calculate the error between the current altitude and the target altitude altitude_error = current_altitude — target_altitude # Calculate the correction value based on the altitude error and the PID constants correction = kpaltitude_error + kiintegral + kd*derivative # Update the integral and derivative values integral += altitude_error derivative = altitude_error — previous_error # Update the previous error value previous_error = altitude_error # Update the desired rotor speed based on the correction value desired_rotor_speed += correction # Limit the desired rotor speed to the maximum and minimum values desired_rotor_speed = max(min(desired_rotor_speed, max_rotor_speed), min_rotor_speed) # Set the rotor speed to the desired value setRotorSpeed(desired_rotor_speed) else: # M
import motor_controller import sensor
Set the minimum safe distance from the ground in meters
min_safe_distance = 2
while True: # Get the current GPS coordinates of the drone current_coordinates = GPS.get_coordinates() # Get the distance from the ground using the ultrasonic sensor distance_from_ground = ultrasonic_sensor.get_distance() # If the distance from the ground is less than the minimum safe distance, issue a command to move up if distance_from_ground < min_safe_distance: drone.move_up() # Else, if the distance from the ground is greater than the minimum safe distance, issue a command to maintain altitude else: drone.maintain_altitude() # Get current orientation data from sensors orientation = sensor.get_orientation() # Control the rotors’ speed and direction to maintain the drone’s altitude and orientation motor_controller.control_rotors(orientation)
def control_rotors(orientation): # Code to control the rotors’ speed and direction based on current orientation data pass
def maintain_altitude(): # Code to maintain the drone’s altitude using sensor data and motor control pass
def move_up(): # Code to increase altitude pass
def move_away(): # Code to move drone away from obstacle pass
def ascend(): # Code to ascend the drone pass
def descend(): # Code to descend the drone pass
def get_orientation(): # Code to get current orientation data from sensors pass
def check_battery_level(): # Code to check current battery level of drone return current_battery_level
def returnToChargingStation(): # Code to navigate drone to charging station location pass
def estimateRemainingFlightTime(battery_level): # Code to estimate remaining flight time based on current battery level pass
def checkWirelessNetwork(): # Code to scan for nearby wireless networks return wireless_network
def connectToWirelessNetwork(network): # Code to connect to a wireless network pass
def transmitEnergy(): # Code to transmit energy back to the house pass
import rotor_controller
def drone_flight_control(): # Get current GPS coordinates current_coordinates = GPS.get_coordinates() # Get distance from ground using sensor data distance_from_ground = sensor.get_distance()
pythonCopy code# Check if distance from ground is safe
if distance_from_ground < SAFE_DISTANCE:
# Issue command to drone to ascend
drone.ascend()
elif distance_from_ground > SAFE_DISTANCE:
# Issue command to drone to descend
drone.descend()
else:
# Maintain current altitude
pass
# Check if drone is within safe proximity of any objects
if sensor.detect_obstacles(current_coordinates):
# Issue command to drone to move away from obstacle
drone.move_away()
else:
# Continue with normal flight
pass
# Control the rotors' speed and direction
rotor_controller.set_rotor_speed(front_left_rotor, front_right_rotor, rear_left_rotor, rear_right_rotor)
rotor_controller.set_rotor_direction(front_left_rotor, front_right_rotor, rear_left_rotor, rear_right_rotor)# Maintain the drone's altitude and orientation
altitude_controller.maintain_altitude()
orientation_controller.maintain_orientation()def set_rotor_speed(front_left_rotor, front_right_rotor, rear_left_rotor, rear_right_rotor): # Code to set the speed of each rotor pass
def set_rotor_direction(front_left_rotor, front_right_rotor, rear_left_rotor, rear_right_rotor): # Code to set the direction of each rotor pass
def maintain_altitude(): # Code to maintain the drone’s altitude pass
def maintain_orientation(): # Code to maintain the drone’s orientation pass
Here is some example Python code for controlling the speed and direction of the rotors on a quadcopter drone:
pythonCopy code# Import the necessary libraries
import time
import RPi.GPIO as GPIO# Set the pin numbers for the motor controls
motor1_pin1 = 17
motor1_pin2 = 18
motor2_pin1 = 22
motor2_pin2 = 23
motor3_pin1 = 24
motor3_pin2 = 25
motor4_pin1 = 4
motor4_pin2 = 3# Set the pin numbering scheme
GPIO.setmode(GPIO.BCM)# Set the pins as output pins
GPIO.setup(motor1_pin1, GPIO.OUT)
GPIO.setup(motor1_pin2, GPIO.OUT)
GPIO.setup(motor2_pin1, GPIO.OUT)
GPIO.setup(motor2_pin2, GPIO.OUT)
GPIO.setup(motor3_pin1, GPIO.OUT)
GPIO.setup(motor3_pin2, GPIO.OUT)
GPIO.setup(motor4_pin1, GPIO.OUT)
GPIO.setup(motor4_pin2, GPIO.OUT)# Define a function to set the speed and direction of the motors
def set_motors(m1_speed, m2_speed, m3_speed, m4_speed):
# Set the speed of the first motor
if m1_speed >= 0:
GPIO.output(motor1_pin1, True)
GPIO.output(motor1_pin2, False) m1_pwm.ChangeDutyCycle(m1_speed) else: GPIO.output(motor1_pin1, False) GPIO.output(motor1_pin2, True) m1_pwm.ChangeDutyCycle(-1*m1_speed)
yamlCopy code# Set the speed of the second motor
if m2_speed >= 0:
GPIO.output(motor2_pin1, True)
GPIO.output(motor2_pin2, False)
m2_pwm.ChangeDutyCycle(m2_speed)
else:
GPIO.output(motor2_pin1, False)
GPIO.output(motor2_pin2, True)
m2_pwm.ChangeDutyCycle(-1*m2_speed)# Set the speed of the third motor
if m3_speed >= 0:
GPIO.output(motor3_pin1, True)
GPIO.output(motor3_pin2, False)
m3_pwm.ChangeDutyCycle(m3_speed)
else:
GPIO.output(motor3_pin1, False)
GPIO.output(motor3_pin2, True)
m3_pwm.ChangeDutyCycle(-1*m3_speed)# Set the speed of the fourth motor
if m4_speed >= 0:
GPIO.output(motor4_pin1, True)
GPIO.output(motor4_pin2, False)
m4_pwm.ChangeDutyCycle(m4_speed)
else: