Real-time Funnel Generation for Restricted Motion Planning

TL;DR

This paper introduces a novel algebraic method using sum-of-squares programming to generate safe, less conservative tracking error bounds for autonomous motion planning, enhancing safety and applicability.

Contribution

It presents a new approach to restrict motion planner behaviors to produce provably safe tracking error bounds, reducing conservatism compared to existing methods.

Findings

Successfully applied to two case studies

Provides acceptable tracking error bounds where previous methods failed

Can be integrated into existing motion planning techniques

Abstract

In autonomous systems, a motion planner generates reference trajectories which are tracked by a low-level controller. For safe operation, the motion planner should account for inevitable controller tracking error when generating avoidance trajectories. In this article we present a method for generating provably safe tracking error bounds, while reducing over-conservatism that exists in existing methods. We achieve this goal by restricting possible behaviors for the motion planner. We provide an algebraic method based on sum-of-squares programming to define restrictions on the motion planner and find small bounds on the tracking error. We demonstrate our method on two case studies and show how we can integrate the method into already developed motion planning techniques. Results suggest that our method can provide acceptable tracking error wherein previous work were not applicable.