CLF-CBF Constraints for Real-Time Avoidance of Multiple Obstacles in Bipedal Locomotion and Navigation
Jinze Liu, Minzhe Li, Jessy W. Grizzle, Jiunn-Kai Huang
Abstract
This paper presents a reactive planning system that allows a Cassie-series bipedal robot to avoid multiple non-overlapping obstacles via a single, continuously differentiable control barrier function (CBF). The overall system detects an individual obstacle via a height map derived from a LiDAR point cloud and computes an elliptical outer approximation, which is then turned into a CBF. The QP-CLF-CBF formalism developed by Ames et al. is applied to ensure that safe trajectories are generated. Safe planning in environments with multiple obstacles is demonstrated both in simulation and experimentally on the Cassie biped.
Topics & Concepts
Differentiable functionObstacle avoidanceComputer scienceObstacleRobotMotion planningTrajectoryControl theory (sociology)Point cloudBiped robotMobile robotFormalism (music)SimulationArtificial intelligenceControl (management)MathematicsPhysicsMathematical analysisVisual artsArtAstronomyMusicalPolitical scienceLawRobotic Path Planning AlgorithmsRobotic Locomotion and ControlRobotics and Sensor-Based Localization