EAST: Environment Aware Safe Tracking using Planning and Control Co-Design

TL;DR

This paper introduces EAST, a novel environment-aware safe tracking method for autonomous robots that integrates planning and control co-design, enabling safe navigation in dynamic, unknown environments with moving obstacles.

Contribution

The paper extends reference governor techniques with control barrier functions for dynamic environments, providing a new integrated approach for safe robot navigation.

Findings

Effective in simulation and real-world tests

Handles complex obstacle configurations and dynamic obstacles

Achieves fast and cautious navigation adaptively

Abstract

This paper considers the problem of autonomous mobile robot navigation in unknown environments with moving obstacles. We propose a new method to achieve environment-aware safe tracking (EAST) of robot motion plans that integrates an obstacle clearance cost for path planning, a convex reachable set for robot motion prediction, and safety constraints for dynamic obstacle avoidance. EAST adapts the motion of the robot according to the locally sensed environment geometry and dynamics, leading to fast motion in wide open areas and cautious behavior in narrow passages or near moving obstacles. Our control design uses a reference governor, a virtual dynamical system that guides the robot's motion and decouples the path tracking and safety objectives. While reference governor methods have been used for safe tracking control in static environments, our key contribution is an extension to dynamic environments using convex optimization with control barrier function (CBF) constraints. Thus, our work establishes a connection between reference governor techniques and CBF techniques for safe control in dynamic environments. We validate our approach in simulated and real-world environments, featuring complex obstacle configurations and natural dynamic obstacle motion.