UAV Depth-Map Path Planning for Real-Time Obstacle Avoidance
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Solution Overview
Problem
Current global path planning methods for UAVs are inadequate for dynamic and unknown environments, as they fail to accurately detect obstacles in real-time, leading to potential collisions.
Innovation Solution
A UAV path planning method that involves acquiring a depth map of the environment, determining a grid map centered on the UAV, calculating candidate flight directions based on passable areas, and selecting an optimal flight direction using a cost function to avoid obstacles, with the ability to re-evaluate and adjust the flight path as necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If global path planning method is used, then the UAV can obtain a desirable flight path in static environment, but it cannot accurately determine obstacles in dynamic and unknown environments
Solution Approach 1:
The patent transitions from static global path planning to dynamic local path planning by continuously updating the grid map based on real-time depth map data. The UAV recalculates flight directions at each grid point during flight, adapting to newly detected obstacles in dynamic environments while maintaining reliable obstacle detection through depth sensing technology.
2Productivity
If global path planning method is used, then a flight path can be obtained in advance, but real-time performance cannot be guaranteed
Solution Approach 1:
The patent performs preliminary grid map generation and candidate flight direction calculation at each grid point before the UAV actually reaches that point. This pre-computation of possible paths allows the UAV to quickly select optimal flight directions in real-time when obstacles are detected, ensuring both high productivity in path planning and rapid response time to dynamic obstacles.
3Reliability
If the UAV continuously updates flight path in real-time, then it can avoid sudden obstacles, but computational complexity increases
Solution Approach 1:
The patent segments the flight path into discrete grid points and divides the environment into a grid map structure. By evaluating candidate flight directions at each individual grid point rather than recalculating the entire path, the algorithm achieves reliable real-time collision avoidance while reducing computational complexity through this segmented, modular approach to path planning.
Data Source
AI summary
Embodiments of the present application relate to the technical field of robot control, and in particular, to an unmanned aerial vehicle (UAV) path planning method and apparatus and a UAV. The UAV path planning method includes: acquiring a depth map of an environment in front of a UAV; acquiring a grid map centered on a body of the UAV according to the depth map; determining candidate flight directions for the UAV according to the grid map; determining an optimal flight direction for the UAV from the candidate flight directions; and controlling the UAV to fly in the optimal flight direction to avoid an obstacle in the environment in front of the UAV. In this way, the embodiments of the present application can accurately determine an obstacle that suddenly appears in an unknown environment and a dynamic environment, so as to achieve real-time path planning.