Reactive task and motion planning for robust whole-body dynamic locomotion in constrained environments

Abstract

Contact-based decision and planning methods are becoming increasingly important to endow higher levels of autonomy for legged robots. Formal synthesis methods derived from symbolic systems have great potential for reasoning about high-level locomotion decisions and achieving complex maneuvering behaviors with correctness guarantees. This study takes a first step toward formally devising an architecture composed of task planning and control of whole-body dynamic locomotion behaviors in constrained and dynamically changing environments. At the high level, we formulate a two-player temporal logic game between the multi-limb locomotion planner and its dynamic environment to synthesize a winning strategy that delivers symbolic locomotion actions. These locomotion actions satisfy the desired high-level task specifications expressed in a fragment of temporal logic. Those actions are sent to a robust finite transition system that synthesizes a locomotion controller that fulfills state reachability constraints. This controller is further executed via a low-level motion planner that generates feasible locomotion trajectories. We construct a set of dynamic locomotion models for legged robots to serve as a template library for handling diverse environmental events. We devise a replanning strategy that takes into consideration sudden environmental changes or large state disturbances to increase the robustness of the resulting locomotion behaviors. We formally prove the correctness of the layered locomotion framework guaranteeing a robust implementation by the motion planning layer. Simulations of reactive locomotion behaviors in diverse environments indicate that our framework has the potential to serve as a theoretical foundation for intelligent locomotion behaviors.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 25, 2022
Source ID
10.1177/02783649221077714

Entities

People

  • Jun Liu
  • Luis Sentis
  • Ufuk Topcu
  • Ye Zhao
  • Yinan Li

Organizations

  • Canada Research Chair
  • Georgia Tech
  • National Science Foundation
  • Natural Sciences and Engineering Research Council
  • Office of Naval Research
  • University of Texas at Austin
  • University of Waterloo

Tags

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control