Hardware-accelerated Ray Tracing for Robot Collision Detection
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Solution Overview
Problem
Existing robotic systems face inefficiencies in collision detection and avoidance due to slow CPU- or GPU-based collision-checking modules, which struggle with complex geometric representations and dynamic environments, leading to inadequate operational performance.
Innovation Solution
Implementing hardware-accelerated ray tracing on graphics processing units (GPUs) to process collision queries faster, enabling the use of complex geometry representations and dynamic obstacle detection, allowing for real-time collision avoidance and motion planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If CPU- or GPU-based collision-checking modules are used, then collision detection can be performed, but the processing speed is too slow to meet real-time operational requirements
Solution Approach 1:
The patent segments the collision detection problem into discrete ray-tracing operations that can be parallelized across multiple GPU cores. Each ray trace operation independently checks for collisions along a specific trajectory, allowing the system to divide the overall collision detection task into many small, concurrently executable units that collectively provide comprehensive real-time collision checking
Solution Approach 2:
The patent replaces traditional CPU-based collision checking algorithms with hardware-accelerated GPU ray-tracing operations. This substitution leverages the parallel processing architecture of GPUs to dramatically accelerate collision detection speed, transforming a sequentially processed mechanical computation into a parallelized hardware operation that meets real-time requirements
2Measurement precision
If complex geometric representations are used to accurately represent robot and obstacles, then collision detection accuracy is improved, but processing complexity and time increase
Solution Approach 1:
The patent uses ray-tracing to create virtual copies of geometric interactions by shooting rays through the scene and calculating intersections with complex surfaces. Instead of directly computing collisions between complex geometric models, the system creates simplified ray representations that interact with the full geometric detail, achieving accurate collision detection without the computational burden of direct complex geometry processing
Solution Approach 2:
The patent changes the fundamental parameter of collision detection from direct geometry-geometry intersection testing to ray-geometry intersection testing. By representing collision queries as rays with simple mathematical definitions rather than complex geometric bodies, the system maintains measurement precision while dramatically reducing processing complexity
3Adaptability or versatility
If traditional collision-checking algorithms are used, then implementation is simpler, but the system cannot handle dynamic environments with changing obstacles and objects
Solution Approach 1:
The patent implements a dynamic collision detection system where ray-tracing operations can be continuously re-executed as the robot and environment change. The system adapts to dynamic environments by updating obstacle positions and re-running ray traces in real-time, allowing the collision detection to automatically adjust to changing conditions without requiring manual reconfiguration or complex predictive modeling
Data Source
AI summary
Use of hardware-accelerated raytracing for intelligent robot task execution is disclosed. In various embodiments, data comprising a geometric representation of a robot and one or more obstacles in a workspace in which the robot is located are used to determine, with respect to a pose of the robot in the workspace, whether the pose is associated with a collision condition with respect to one or more of the one or more obstacles, at least in part by performing hardware accelerated ray tracing with respect to rays originating from each of a plurality of points associated with the robot.