Adaptive Tracking Control of On-Line Path Planners: Velocity Fields and Navigation Functions

Abstract

Traditionally, robot control research has focused on the position tracking problem where the objective is to force the robot's end-effector to follow an a priori known desired time dependent trajectory. Motivated by task objectives that are more effectively described by on-line, state-dependent trajectories, two adaptive tracking controllers are developed in this paper that accommodate on-line path planning objective. An example adaptive controller is first modified to achieve velocity field tracking in the presence of parametric uncertainty in the robot dynamics. The development aims to relax the typical assumption that the integral of the velocity field is bounded by incorporating a norm- squared gradient term in the control design so that the boundedness of all signals can be proven. An extension is then provided that targets the trajectory planning problem where the task objective can be described as the desire to move to a goal configuration while avoiding known obstacles. Specifically, an adaptive navigation function based controller is designed to provide a path from an initial condition inside the free configuration space of the robot manipulator to the goal configuration. Experimental results for each controller are provided to illustrate proof of validation of the approaches.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA465704

Entities

People

  • Bin Xian
  • D. M. Dawson
  • M. L. Mcintyre
  • W. E. Dixon

Organizations

  • Clemson University

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Collision Avoidance
  • Collisions
  • Control
  • Data Acquisition
  • Dynamics
  • Engineering
  • Inequalities
  • Manipulators
  • Models
  • Motion Planning
  • Navigation
  • Robots
  • Stratified Fluids
  • Trajectories
  • Universities

Readers

  • Calculus or Mathematical Analysis
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers