Adaptive Semi-Autonomous Teleoperation of a Multi-Agent Robotic System

Abstract

The primary objective of this paper is to develop an adaptive bilateral impedance control method for a team of mobile robotic agents, which implements formation control, cooperative grasping force compensation, and operator induced error compensation for unconstrained, constrained, and transition motions. In this approach, a leader robot is selected and teleoperated by an operator and the follower robots are autonomously coordinated to make a formation to perform a task of cooperatively transferring an object. By estimating the target dynamics, the bilateral impedances of the system are adjusted to assist the operator in determining grasping forces to have a secure grip of the object. In addition, the formation can be reconfigured to avoid collisions with stationary obstacles and among the member robots. The performance of the developed method was investigated through haptic simulations. In the simulation study, a haptic device was used as the master robot, and three virtual omnidirectional mobile platforms were employed to transfer an object. The simulation results demonstrate stable grasping motions of the team of the mobile robot and position and force errors minimized by adapting the bilateral impedances of the system.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA505730

Entities

People

  • Jae H. Chung
  • Norman P. Coleman

Organizations

  • United States Army Armament Research, Development and Engineering Center

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Air Resistance
  • Collision Avoidance
  • Collisions
  • Compensation
  • Coordinate Systems
  • Directional
  • Dynamics
  • Environment
  • Human Supervisory Control
  • Impedance
  • Materials
  • Motor Skills
  • Orientation (Direction)
  • Simulations
  • Teleoperation
  • Transportation

Readers

  • Robotics and Automation.

Technology Areas

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