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Visual guided adaptive robotic interceptions with occluded target motion estimations

Yushing Cheung, Yating Huang, Jenn-Jier James Lien

发表年份
2015
引用次数
4

摘要

To increase an industrial production rate in a robotic operation, automated assembly tasks on production lines require the operation being performed while a target is still moving. Due to complicated factory environments and missions, unexpected vision occlusion, switching grippers, and grasping the target in motion are demanded. Therefore, a vision guided robotic system consisting of a joint space adaptive controller and a visual target motion estimator is proposed. With the visual target motion estimator, current target velocities and positions are estimated. Regarding the current target velocities and positions, desired robotic joint velocities and positions are computed even if vision is occluded. Moreover, by tracking the desired joint velocities and positions with the adaptive controller, a robotic end-effector is controlled to catch the target even if target and gripper parameters are uncertain. In experiments, grasping the moving target at different speeds with the different grippers for different lengths of occlusion time by using our proposed system were presented for performance evaluations according to its efficiency and robustness.

关键词

GrippersComputer visionArtificial intelligenceMotion blurRobustness (evolution)EstimatorComputer scienceVisual servoingRobot end effectorRobot

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