Robust Robot Control Using Multiple Model-Based Policy Optimization and Fast Value Function-Based Planning

Abstract

This report describes the research findings of Team Steel, the group led by PI Christopher G. Atkeson in the DARPA Virtual Robotics Challenge (VRC). They developed human-like walking and robust walking on rough terrain, and automated driving in the VRC context. They developed a rough terrain footstep planner, a decoupled approach to state estimation, and an optimization based real-time walking controller for a full size 3D humanoid robot. They showed that optimal stepping trajectories and trajectory cost for a walking biped robot on rough terrain can be encoded as simple quadratic functions of initial state and footstep sequence.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2014
Accession Number
ADA598420

Entities

People

  • Christopher G. Atkeson

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Angular Momentum
  • Bodies
  • Collision Avoidance
  • Computer Programming
  • Dynamic Programming
  • Government Procurement
  • Governments
  • Information Exchange
  • Motion Planning
  • Optimization
  • Robotics
  • Robots
  • Sequences
  • Trajectories

Readers

  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy