Modular Autonomous Drone With AI Vision Flightpath Control
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Solution Overview
Problem
Current drone technologies require human input for navigation, especially in racing scenarios, which limits speed and agility, and lack efficient methods for autonomous operation, particularly in complex environments.
Innovation Solution
An autonomous drone system equipped with an AI controller that uses Computer Vision from multiple cameras to determine flight paths in real-time, allowing the drone to navigate without human input and switch between autonomous and remote-control modes seamlessly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If human pilots remotely control drones for racing, then navigation capability is achieved, but speed and agility are limited due to human reaction time
Solution Approach 1:
The drone is equipped with an AI controller that enables autonomous navigation and racing without human intervention. The AI controller processes visual data from cameras, determines flight paths, and controls flight parameters independently, allowing the drone to serve itself in navigation tasks and eliminate human reaction time limitations.
Solution Approach 2:
The patent replaces the mechanical human control system with an AI-based autonomous control system. The AI controller uses computer vision algorithms to perceive the environment and makes real-time decisions, substituting human neural processing with automated computational processing that operates at machine speed.
2Productivity
If autonomous operation is implemented, then speed and agility improve, but system complexity increases due to AI controller requirements
Solution Approach 1:
The AI controller is designed as a universal module that can be integrated into various drone platforms. It performs multiple functions including visual processing, path planning, flight control, and mode switching, consolidating complex autonomous operations into a single multi-functional component that can be applied across different drone configurations.
Solution Approach 2:
The AI controller acts as an intermediary between the drone's sensors (cameras) and actuators (motors). It processes visual information and translates it into flight commands, mediating between perception and action while managing the complexity of autonomous navigation through a dedicated control layer.
3Adaptability or versatility
If modular design is used with removable AI controller, then adaptability improves, but connection reliability may be affected by physical coupling/decoupling
Solution Approach 1:
The system implements dynamic reconfigurability where the AI controller can be physically coupled or decoupled from the flight controller based on operational needs. The coupling mechanism includes electrical connections that are established or disconnected through physical engagement, allowing the system to dynamically switch between autonomous and remote-control modes.
Solution Approach 2:
The AI controller is designed as a separable module that can be extracted from the flight controller. The coupling mechanism allows the AI controller to be physically removed or attached, enabling users to extract the autonomous functionality when not needed and retain only the basic flight controller for simple remote-control operations.
Data Source
AI summary
An autonomous quadcopter has four motors, each motor coupled to a corresponding propeller and a flight controller coupled to the four motors to provide input to the four motors to control flight. The autonomous quadcopter also has a plurality of cameras and an Artificial Intelligence (AI) controller coupled to the plurality of cameras to receive input from the plurality of cameras, determine a flightpath for the autonomous quadcopter according to the input from the plurality of cameras, and provide commands to the flight controller to direct the flight controller to follow the flightpath.