Voxel-Based Moving Body Path Control for Accurate Collision Checks
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Solution Overview
Problem
Existing path planning algorithms, such as the probabilistic roadmap (PRM) algorithm, struggle with inaccurate collision detection due to the use of bounding boxes that fail to accurately represent complex moving bodies, leading to low detection accuracy and inefficient path planning.
Innovation Solution
The method employs voxels to accurately represent the appearance of moving bodies and obstacles, utilizing a mapping relationship between voxels and moving paths to quickly determine valid paths, reducing the search range and conserving computing resources through table lookup.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a bounding box algorithm is used for collision detection, then the detection process is simple to implement, but the detection accuracy is low because the bounding box cannot accurately represent complex moving bodies
Solution Approach 1:
The patent segments the continuous space into discrete voxel units, transforming the complex collision detection problem into a simpler voxel-based representation. Each voxel acts as an independent unit that can be efficiently queried, replacing the inaccurate bounding box approach while maintaining computational simplicity.
Solution Approach 2:
The patent creates a voxel copy or representation of the actual moving body and obstacle geometries. Instead of directly processing complex geometric shapes, the system uses voxelized copies that preserve the essential spatial information needed for accurate collision detection while enabling faster computation.
2Measurement precision
If a comprehensive path planning search is performed to ensure accuracy, then the path planning precision is high, but the computing time and resources increase significantly
Solution Approach 1:
The patent performs preliminary voxelization of the environment and pre-computes the voxel-moving path mapping relationship before actual path planning occurs. This preliminary action prepares the data structure in advance, allowing the planning algorithm to quickly query valid paths without performing comprehensive searches during real-time operation.
Solution Approach 2:
By segmenting the path planning problem into voxel-based discrete steps and using pre-computed mapping relationships, the system divides the comprehensive search into manageable segments. This allows the algorithm to efficiently identify valid paths by checking voxel occupancy rather than performing exhaustive geometric collision checks.
3Measurement precision
If a detailed collision detection algorithm is used to improve accuracy, then the detection precision increases, but the computing resources required increase significantly
Solution Approach 1:
The patent replaces complex geometric collision detection algorithms with a simplified voxel-based detection mechanism. Instead of performing detailed geometric intersection calculations, the system uses discrete voxel occupancy checks, which consume fewer computing resources while maintaining accurate collision detection capability.
Solution Approach 2:
The patent changes the representation parameters from continuous geometric coordinates to discrete voxel indices. This parameter transformation enables the use of simpler data structures and faster lookup operations, reducing computing resource consumption while preserving the essential spatial information needed for accurate collision detection.
Data Source
AI summary
A method for controlling movement of a moving body includes: obtaining a first voxel set of an obstacle, where the first voxel set includes at least one first voxel that identifies the obstacle in space in which the moving body is located; determining a valid moving path based on a mapping relationship between a voxel and a moving path and the first voxel set; and controlling the moving body to move along the valid moving path.