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MANIPULATION

Uncertainty-Aware Manipulation Planning Using Gravity and Environment Geometry

Felix von Drigalski, Kazumi Kasaura, Cristian C. Beltran-Hernandez, Masashi Hamaya, Kazutoshi Tanaka, Takamitsu Matsubara

发表年份
2022
引用次数
8
访问权限
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摘要

Factory automation robot systems often depend on specially-made jigs that precisely position each part, which increases the system's cost and limits flexibility. We propose a method to determine the 3D pose of an object with high precision and confidence, using only parallel robotic grippers and no parts-specific jigs. Our method automatically generates a sequence of actions that ensures that the real-world position of the physical object matches the system's assumed pose to sub-mm precision. Furthermore, we propose the use of “extrinsic” actions, which use gravity, the environment and the gripper geometry to significantly reduce or even eliminate the uncertainty about an object's pose. We show in simulated and real-robot experiments that our method outperforms our previous work, at success rates over 95%.

关键词

GrippersFlexibility (engineering)Object (grammar)Position (finance)Factory (object-oriented programming)RobotComputer scienceAutomationComputer visionArtificial intelligence

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