Autonomous legged hill ascent

Abstract

This paper reports on an autonomous ascent by a legged robotic platform in outdoor forested terrain. Two controllers govern the integration of online inertial measurement unit and light detection and ranging sensor signals into commands for climbing by means of an abstracted (unicycle) representation of the platform in support of different performance goals: a kinematic version for endurance and a dynamic version for speed. These control laws, backed by a suite of formal correctness guarantees, encourage a stripped‐down sensory suite supporting a simplified world model whose departures from the actual physical environment are handled by the mechanical competence of the legged platform. Both behaviors are implemented on a version of the legged RHex platform, and experiments spanning almost a kilometer (thousands of body lengths) in various challenging settings are conducted.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 23, 2018
Source ID
10.1002/rob.21779

Entities

People

  • Aaron M. Johnson
  • B. Deniz Ilhan
  • Daniel E. Koditschek

Organizations

  • Air Force Office of Scientific Research
  • Carnegie Mellon University
  • National Science Foundation
  • United States Army Research Laboratory
  • University of Pennsylvania

Tags

Readers

  • Radar Systems Engineering.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

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