Uncalibrated Eye-in-Hand Visual Servoing

Abstract

In this paper we present newuncalibrated control schemes for visionguided robotic tracking of a moving target using a moving camera. These control methods are applied to an uncalibrated robotic system with eye-in-hand visual feedback. Without a priori knowledge of the robot's kinematic model or camera calibration, the system is able to track a moving object through a variety of motions and maintain the object's image features in a desired position in the image plane. These control schemes estimate the system Jacobian as well as changes in target features due to target motion. Four novel strategies are simulated and a variety of parameters are investigated with respect to performance. Simulation results suggest that a Gauss? Newton method utilizing a partitioned Broyden's method for model estimation provides the best steady-state tracking behavior.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2003
Accession Number
ADA575014

Entities

People

  • Harvey Lipkin
  • Jenelle A. Piepmeier

Organizations

  • United States Naval Academy

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Automation
  • Calibration
  • Computer Vision
  • Control Systems
  • Estimators
  • Filters
  • Kalman Filters
  • Moving Targets
  • Robotics
  • Robots
  • Simulations
  • Steady State
  • Targets
  • United States Naval Academy
  • Visual Servoing

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Linear Algebra
  • Robotics and Automation.

Technology Areas

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