Cassie Autonomously Navigates in Four Long Corridors (200 meters)

Cassie Blue autonomously navigates on the second floor of the Ford Robotics Building at the University of Michigan. The total traverse distance is 200 m (656.168 feet).

The LiDAR and IMU data are fused in real-time to form an elevation map. The system consists of a low-frequency planning thread (5 Hz) to find an asymptotically optimal path and a high-frequency reactive thread (300 Hz) to accommodate robot deviation. The planning thread includes: a multi-layer local map to compute traversability for the robot on the terrain; an anytime omnidirectional Control Lyapunov Function (CLF) for use with a Rapidly Exploring Random Tree Star (RRT*) that generates a vector field for specifying motion between nodes; a sub-goal finder when the final goal is outside of the current map; and a finite-state machine to handle high-level mission decisions. The paper [https://arxiv.org/abs/2108.06699] provides full details on the reactive planning system.

The software for the planning package is public: [https://github.com/UMich-BipedLab/CLF_reactive_planning_system]

Видео Cassie Autonomously Navigates in Four Long Corridors (200 meters) канала Michigan Robotics: Dynamic Legged Locomotion Lab