RTPD: Penetration Depth calculation using Hardware accelerated Ray-Tracing

TL;DR

This paper presents a novel RT-core-based algorithm for calculating penetration depth, significantly outperforming existing GPU methods in speed and efficiency across various scenes and GPU generations.

Contribution

The paper introduces a new algorithm that leverages hardware-accelerated ray-tracing cores for faster and more efficient penetration depth computation.

Findings

Up to 37.66 times faster than state-of-the-art methods

Outperforms conventional GPU implementations by up to 5.33 times

Demonstrates broad applicability of RT-cores in computational tasks

Abstract

Penetration depth calculation quantifies the extent of overlap between two objects and is crucial in fields like simulations, the metaverse, and robotics. Recognizing its significance, efforts have been made to accelerate this computation using parallel computing resources, such as CPUs and GPUs. Unlike traditional GPU cores, modern GPUs incorporate specialized ray-tracing cores (RT-cores) primarily used for rendering applications. We introduce a novel algorithm for penetration depth calculation that leverages RT-cores. Our approach includes a ray-tracing based algorithm for penetration surface extraction and another for calculating Hausdorff distance, optimizing the use of RT-cores. We tested our method across various generations of RTX GPUs with different benchmark scenes. The results demonstrated that our algorithm outperformed a state-of-the-art penetration depth calculation method and conventional GPU implementations by up to 37.66 and 5.33 times, respectively. These findings demonstrate the efficiency of our RT core-based method and suggest broad applicability for RT-cores in diverse computational tasks.