Dynamically Feasible Path Planning in Cluttered Environments via Reachable Bezier Polytopes

TL;DR

This paper introduces a method using reachable Bezier polytopes and GPU acceleration to generate collision-free, dynamically feasible paths for robots in cluttered environments, demonstrated on 3D hopping tasks.

Contribution

It presents a novel approach combining reachable Bezier polytopes with GPU computing for real-time, feasible path planning in complex environments.

Findings

Efficient path planning meeting real-time constraints.

Successful demonstration on 3D hopping in cluttered spaces.

Framework ensures collision avoidance and dynamic feasibility.

Abstract

The deployment of robotic systems in real world environments requires the ability to quickly produce paths through cluttered, non-convex spaces. These planned trajectories must be both kinematically feasible (i.e., collision free) and dynamically feasible (i.e., satisfy the underlying system dynamics), necessitating a consideration of both the free space and the dynamics of the robot in the path planning phase. In this work, we explore the application of reachable Bezier polytopes as an efficient tool for generating trajectories satisfying both kinematic and dynamic requirements. Furthermore, we demonstrate that by offloading specific computation tasks to the GPU, such an algorithm can meet tight real time requirements. We propose a layered control architecture that efficiently produces collision free and dynamically feasible paths for nonlinear control systems, and demonstrate the framework on the tasks of 3D hopping in a cluttered environment.