UAV Collision Avoidance Using Dynamic Potential Fields
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Solution Overview
Problem
Existing collision avoidance algorithms for unmanned aerial vehicles (UAVs) are inadequate in densely populated areas with unpredictable obstacles, failing to effectively prevent collisions with both stationary and moving objects, particularly in complex urban environments.
Innovation Solution
A collision avoidance algorithm using a potential field method that computes attractive and repulsive forces based on current positional information, obstacle detection with LiDAR, and Kalman filtering to estimate obstacle velocity, allowing for adaptive control to avoid collisions in densely populated areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a general potential field algorithm is used for collision avoidance, then the algorithm is simple to implement, but it performs poorly in avoiding moving obstacles
Solution Approach 1:
The patent transforms the static potential field into a dynamic one by incorporating relative velocity information of obstacles. The repulsive force is no longer solely based on distance but also on the relative velocity between the UAV and obstacles, making the field adaptive to moving obstacles while maintaining the overall algorithm structure
Solution Approach 2:
The patent modifies the potential field parameters by introducing velocity-dependent terms. The repulsive potential function is enhanced to include relative velocity components, changing the field characteristics from static to dynamic without fundamentally altering the potential field methodology
2Adaptability or versatility
If existing collision avoidance algorithms are used in densely populated areas, then the algorithms can handle simple environments, but they fail to effectively prevent collisions with unpredictable obstacles
Solution Approach 1:
The patent makes the potential field dynamic by incorporating real-time velocity information of obstacles. This allows the algorithm to adapt to changing environments and moving obstacles in densely populated areas, improving reliability while maintaining adaptability to different scenarios
Solution Approach 2:
The patent introduces velocity feedback from obstacle tracking into the potential field calculation. By continuously monitoring and incorporating obstacle motion information, the algorithm can respond to unpredictable movements in complex environments, enhancing both adaptability and collision prevention effectiveness
3Reliability
If the repulsive force coefficient is increased to avoid obstacles more aggressively, then collision avoidance with stationary obstacles improves, but the UAV may get trapped in local minima
Solution Approach 1:
The patent makes the repulsive force dynamic by incorporating relative velocity. When the UAV approaches a stationary obstacle, the full repulsive force applies. When approaching moving obstacles, the velocity-dependent term modulates the force, preventing excessive repulsion that could cause local minima trapping while maintaining effective avoidance
Solution Approach 2:
The patent dynamically adjusts the effective repulsive force parameter based on obstacle velocity. This parameter modulation allows the system to maintain strong avoidance capability for stationary obstacles while reducing aggressive repulsion for moving obstacles, thereby preventing local minima entrapment
Data Source
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AI summary
Provided is a method of avoiding collision of an unmanned aerial vehicle with an obstacle, the method including: calculating two potential fields using current positional information of the unmanned aerial vehicle, a target point that is set, and positional information of the obstacle measured by a sensor; computing an attractive force and a repulsive force by differentiating the computed potential fields, respectively; computing a direction of a potential force that results from adding up the computed attractive force and repulsive force; and performing control that brings about a change from the computed direction of the potential force to a direction in which the unmanned aerial vehicle moves.