Dynamic Gap: Safe Gap-based Navigation in Dynamic Environments

TL;DR

This paper introduces Dynamic Gap, a novel local planner for navigation in unknown dynamic environments that guarantees collision avoidance through formal analysis of gap evolution, outperforming existing planners in success rate.

Contribution

The paper presents a formal, gap-based local planner that models free space evolution over time, providing provable safety guarantees in dynamic environments.

Findings

Achieves the highest success rate in simulation benchmarks

Provides formal collision-free guarantees

Outperforms existing local planners in dynamic scenarios

Abstract

This paper extends the family of gap-based local planners to unknown dynamic environments through generating provable collision-free properties for hierarchical navigation systems. Existing perception-informed local planners that operate in dynamic environments rely on emergent or empirical robustness for collision avoidance as opposed to performing formal analysis of dynamic obstacles. In addition to this, the obstacle tracking that is performed in these existent planners is often achieved with respect to a global inertial frame, subjecting such tracking estimates to transformation errors from odometry drift. The proposed local planner, dynamic gap, shifts the tracking paradigm to modeling how the free space, represented as gaps, evolves over time. Gap crossing and closing conditions are developed to aid in determining the feasibility of passage through gaps, and a breadth of simulation benchmarking is performed against other navigation planners in the literature where the proposed dynamic gap planner achieves the highest success rate out of all planners tested in all environments.