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- W1994479632 abstract "ABSTRACT This paper describes an integral approach to the acquisition of randomly moving objects with a robot. The acquisitionproblem is phrased as a feedback control problem that explicitly models the target dynamics, butjustifiably excludes the robotdynamics. The target's position deviation with respect to the robot is sensed by a camera mounted within the end-effector andused to servo the robot governed by controller-observer pairs. Acquisition takes place once the system is sufficiently certainabout the target's motion pattern. A good balance is found for the trade-off in this phase between a decreasing field of viewfor the camera and the need to get close for acquisition. The approach was tested on a PUMA-560 robot with a gripper mount-ed camera. The experimental system can acquire objects that are moving randomly on a table; an early version was integratedin a kitting robot cell [15]. 1. INTRODUCTION The success for flexible automation applications (e.g. kitting robots [15]) is greatly dependent on their reliability androbustness against those uncertainties which are inevitable in any realistic environment. The use of vision as a sensor can sig-nificantly improve the robustness of applications by measuring and correcting for deviations from expectations. As such, vi-sual tracking and acquisition systems have received a lot of attention (for recent work see[1]-[7]). Important aspects for visualservoing systems are the need for fast recognition and control to keep up with the target's motion.Most implementations to date have focused on solely the tracking components and used one or more stationary cam-eras to establish position estimates of the target object. To speed up the visual recognition, most approaches rely on featureextraction, requiring a priori knowledge of the object shape. In addition, the object needs to be in sharp focus all the time forthe features to stand out. A notable exception to this is the optic flow approach of Allen et. al.[3], which directly estimatesoptic flow and deduces motion from the flow centroids. However, this is still a time consuming process with motion estimates" @default.
- W1994479632 created "2016-06-24" @default.
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- W1994479632 date "1993-08-06" @default.
- W1994479632 modified "2023-09-23" @default.
- W1994479632 title "<title>Acquisition of randomly moving objects by visual guidance</title>" @default.
- W1994479632 doi "https://doi.org/10.1117/12.150205" @default.
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