Desensitization of Camera-Aided Manipulation to Target Specification Errors

Applications of vision-based remotely operated robotic systems range from planetary exploration to hazardous waste remediation. For space applications, where communication time lags are large, the target selection and robot positioning tasks may be performed sequentially, differing from conventional telerobotic maneuvers. For these point-and-move systems, the desired target must be defined in the image plane of the cameras either by an operator or through image processing software. Ambiguity of the target specification will naturally lead to end-effector positioning errors. In this paper, the target specification error covariance is shown to transform linearly to the end-effector positioning error. In addition, a methodology for optimal estimation of camera-view parameters of a vision-based robotic system based on target specification errors is presented. The proposed strategy is based on minimizing the end-effector error covariance matrix. Experimental results are presented demonstrating an increase in end-effector positioning, compared to traditional view parameter estimation by up to 32%.