RoboGPU: Accelerating GPU Collision Detection for Robotics

TL;DR

RoboGPU enhances GPU-based collision detection for robotics, achieving significant speedups over traditional methods and adaptable to evolving algorithms, thus improving real-time robotic motion planning and localization.

Contribution

The paper introduces RoboGPU, a novel GPU architecture with RoboCore that accelerates collision detection and other robotics tasks, surpassing existing GPU and hardware accelerators.

Findings

RoboCore is 3.1× faster than RTA units for collision queries.

RoboCore achieves 14.8× speedup over CUDA baseline.

RoboGPU matches hardware accelerators and improves robotics task performance.

Abstract

Autonomous robots are increasingly prevalent in our society, emerging in medical care, transportation vehicles, and home assistance. These robots rely on motion planning and collision detection to identify a sequence of movements allowing them to navigate to an end goal without colliding with the surrounding environment. While many specialized accelerators have been proposed to meet the real-time requirements of robotics planning tasks, they often lack the flexibility to adapt to the rapidly changing landscape of robotics and support future advancements. However, GPUs are well-positioned for robotics and we find that they can also tackle collision detection algorithms with enhancements to existing ray tracing accelerator (RTA) units. Unlike intersection tests in ray tracing, collision queries in robotics require control flow mechanisms to avoid unnecessary computations in each query. In this work, we explore and compare different architectural modifications to address the gaps of existing GPU RTAs. Our proposed RoboGPU architecture introduces a RoboCore that computes collision queries 3.1$\times$ faster than RTA implementations and 14.8$\times$ faster than a CUDA baseline. RoboCore is also useful for other robotics tasks, achieving 3.6$\times$ speedup on a state-of-the-art neural motion planner and 1.1$\times$ speedup on Monte Carlo Localization compared to a baseline GPU. RoboGPU matches the performance of dedicated hardware accelerators while being able to adapt to evolving motion planning algorithms and support classical algorithms.