Hardware-Accelerated Ray Tracing for Discrete and Continuous Collision Detection on GPUs

2024-09-16

IEEE International Conference on Robotics and Automation

AI Summary

To address the low efficiency of collision detection in robot scenarios with high geometric complexity, this work pioneers the direct utilization of GPU hardware ray tracing (RT Core) for discrete collision detection between voxelized meshes, and extends it to continuous collision detection along piecewise linear and quadratic B-spline trajectories. The method integrates bounding volume hierarchy (BVH) acceleration, volumetric coverage error analysis, and CUDA-specific optimizations to balance accuracy and scalability. Experiments on a representative scenario comprising 24k robot triangles and 190k obstacle triangles demonstrate a 2.8× speedup for batched discrete collision detection and up to a 7× speedup for continuous collision detection. Furthermore, the trade-off between accuracy and performance is systematically quantified. This work establishes a new paradigm for real-time, high-fidelity robotic collision detection.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Search and Optimization: Mixed Discrete/Continuous Search
• Computer Vision: Vision for Robotics & Autonomous Driving

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

This paper presents a set of simple and intuitive robot collision detection algorithms that show substantial scaling improvements for high geometric complexity and large numbers of collision queries by leveraging hardware-accelerated ray tracing on GPUs. It is the first leveraging hardware-accelerated ray-tracing for direct volume mesh-to-mesh discrete collision detection and applying it to continuous collision detection. We introduce two methods: Ray-Traced Discrete-Pose Collision Detection for exact robot mesh to obstacle mesh collision detection, and Ray-Traced Continuous Collision Detection for robot sphere representation to obstacle mesh swept collision detection, using piecewise-linear or quadratic B-splines. For robot link meshes totaling 24k triangles and obstacle meshes of over 190k triangles, our methods were up to 2.8 times faster in batched discrete-pose queries than a state-of-the-art GPU-based method using a sphere robot representation. For the same obstacle mesh scene, our sphere-robot continuous collision detection was up to 7 times faster depending on trajectory batch size. We also performed detailed measurements of the volume coverage accuracy of various sphere/mesh pose/path representations to provide insight into the tradeoffs between speed and accuracy of different robot collision detection methods.

Problem

• Accelerating robot collision detection using GPU ray tracing
• Enabling discrete and continuous collision detection for complex geometries
• Improving speed and accuracy tradeoffs in collision queries

Innovation

• GPU hardware-accelerated ray tracing
• Discrete mesh-to-mesh collision detection
• Continuous sphere-mesh swept detection