Safe Interval Motion Planning for Quadrotors in Dynamic Environments

TL;DR

This paper introduces a novel safe interval motion planning framework for quadrotors navigating dynamic environments, combining graph search and gradient optimization to ensure safety, optimality, and real-time performance.

Contribution

It presents a two-stage planning approach with a dynamic visibility graph and UTVDe for complete, optimal, and efficient trajectory generation in dynamic settings.

Findings

Achieves over 95% success rate in various dynamic environments.

Outperforms existing methods in safety and efficiency.

Demonstrates effectiveness in both simulation and real-world tests.

Abstract

Trajectory generation in dynamic environments presents a significant challenge for quadrotors, particularly due to the non-convexity in the spatial-temporal domain. Many existing methods either assume simplified static environments or struggle to produce optimal solutions in real-time. In this work, we propose an efficient safe interval motion planning framework for navigation in dynamic environments. A safe interval refers to a time window during which a specific configuration is safe. Our approach addresses trajectory generation through a two-stage process: a front-end graph search step followed by a back-end gradient-based optimization. We ensure completeness and optimality by constructing a dynamic connected visibility graph and incorporating low-order dynamic bounds within safe intervals and temporal corridors. To avoid local minima, we propose a Uniform Temporal Visibility Deformation (UTVD) for the complete evaluation of spatial-temporal topological equivalence. We represent trajectories with B-Spline curves and apply gradient-based optimization to navigate around static and moving obstacles within spatial-temporal corridors. Through simulation and real-world experiments, we show that our method can achieve a success rate of over 95% in environments with different density levels, exceeding the performance of other approaches, demonstrating its potential for practical deployment in highly dynamic environments.