A global and local robot tracking and control strategy using multisensory inputs

A dual phase robot tracking and control strategy is proposed where a global trajectory of the robot is initially estimated in phase one using absolute location information provided by fixed, "far-away" sensors and then in phase two, a fine-motion reactive tracker is invoked to compensate for the local deviations about the globally estimated trajectory from phase one. This dual phase tracking strategy reduces both the tracking error and the capture time of the target by the robot, compared to the operation of either mode of tracking (global or local) independently. The sensory information provided by the multiple sensors, disparate or redundant, is fused together to increase the reliability of the system.<<ETX>>

[1]  William J. Wilson,et al.  Direct dynamic control of a robot using an end-point mounted camera and Kalman filter position estimation , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[2]  George J. Klir,et al.  A principle of uncertainty and information invariance , 1990 .

[3]  Christopher Bowman Maximum likelihood track correlation for multisensor integration , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[4]  Ronald Mucci,et al.  Target parameter estimation using measurements acquired with a small number of sensors , 1983 .

[5]  G. Klir,et al.  MEASURES OF UNCERTAINTY AND INFORMATION BASED ON POSSIBILITY DISTRIBUTIONS , 1982 .

[6]  Chuen-Chien Lee FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[7]  W. Thomas Miller,et al.  Real-time application of neural networks for sensor-based control of robots with vision , 1989, IEEE Trans. Syst. Man Cybern..

[8]  P. K. Khosla,et al.  Adaptive Robotic Visual Tracking , 1991, 1991 American Control Conference.

[9]  Lee E. Weiss,et al.  Adaptive Visual Servo Control of Robots , 1983 .

[10]  Nikolaos Papanikolopoulos,et al.  Adaptive robotic visual tracking: theory and experiments , 1993, IEEE Trans. Autom. Control..

[11]  I. Turksen Measurement of membership functions and their acquisition , 1991 .

[12]  Hirokazu Ihara,et al.  A track correlation algorithm for multi-sensor integration , 1987 .

[13]  John Todd Feddema,et al.  Real-time visual feedback control for hand-eye coordinated robotic systems , 1989 .