High-level planner synthesis for whole-body locomotion in unstructured environments

Abstract

Contact-based decision and planning methods are increasingly being sought for task execution in humanoid robots. However, formal methods from the verification and synthesis communities have not been yet incorporated into the motion planning sequence for complex mobility behaviors in humanoid robots. This study takes a step toward formally synthesizing high-level reactive task planners for whole-body locomotion in unstructured environments. We formulate a two-player temporal logic game between the contact planner and its possibly adversarial environment. The resulting discrete planner satisfies the given task specifications expressed in a fragment of temporal logic. The resulting commands are executed by a low-level 3D phase-space motion planner algorithm. We devise various low-level locomotion modes based on centroidal momentum dynamics. Provable correctness of the low-level execution of the synthesized discrete task planner is guaranteed through the so-called simulation relations. Simulations of dynamic locomotion in unstructured environments support the effectiveness of the hierarchical planner protocol.