Towards Safe Locomotion Navigation in Partially Observable Environments with Uneven Terrain

TL;DR

This paper introduces an integrated planning framework combining symbolic task planning and phase-space motion planning to enable safe, dynamic bipedal robot locomotion in partially observable, uneven terrains with multi-level safety guarantees.

Contribution

It presents a layered planning approach that integrates belief estimation, formal task synthesis, and safe trajectory generation for complex environments.

Findings

Successful simulation of Cassie robot navigating dynamic obstacles

Effective belief-based obstacle localization and safety guarantees

Trajectory planning meeting balancing safety and maneuverability

Abstract

This study proposes an integrated task and motion planning method for dynamic locomotion in partially observable environments with multi-level safety guarantees. This layered planning framework is composed of a high-level symbolic task planner and a low-level phase-space motion planner. A belief abstraction at the task planning level enables belief estimation of dynamic obstacle locations and guarantees navigation safety with collision avoidance. The high-level task planner, i.e., a two-level navigation planner, employs linear temporal logic for a reactive game synthesis between the robot and its environment while incorporating low-level safe keyframe policies into formal task specification design. The synthesized task planner commands a series of locomotion actions including walking step length, step height, and heading angle changes, to the underlying keyframe decision-maker, which further determines the robot center-of-mass apex velocity keyframe. The low-level phase-space planner uses a reduced-order locomotion model to generate non-periodic trajectories meeting balancing safety criteria for straight and steering walking. These criteria are characterized by constraints on locomotion keyframe states, and are used to define keyframe transition policies via viability kernels. Simulation results of a Cassie bipedal robot designed by Agility Robotics demonstrate locomotion maneuvering in a three-dimensional, partially observable environment consisting of dynamic obstacles and uneven terrain.