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Vision‐Based Intelligent Perceiving and Planning System of a 7‐DoF Collaborative Robot

Linfeng Xu, Gang Li, Peiheng Song, Weixiang Shao

发表年份
2021
引用次数
3
访问权限
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摘要

In this paper, an intelligent perceiving and planning system based on deep learning is proposed for a collaborative robot consisting of a 7-DoF (7-degree-of-freedom) manipulator, a three-finger robot hand, and a vision system, known as IPPS (intelligent perceiving and planning system). The lack of intelligence has been limiting the application of collaborative robots for a long time. A system to realize "eye-brain-hand" process is crucial for the true intelligence of robots. In this research, a more stable and accurate perceiving process was proposed. A well-designed camera system as the vision system and a new hand tracking method were proposed for operation perceiving and recording set establishment to improve the applicability. A visual process was designed to improve the accuracy of environment perceiving. Besides, a faster and more precise planning process was proposed. Deep learning based on a new CNN (convolution neural network) was designed to realize intelligent grasping planning for robot hand. A new trajectory planning method of the manipulator was proposed to improve efficiency. The performance of the IPPS was tested with simulations and experiments in a real environment. The results show that IPPS could effectively realize intelligent perceiving and planning for the robot, which could realize higher intelligence and great applicability for collaborative robots.

关键词

Computer scienceArtificial intelligenceRobotProcess (computing)Convolutional neural networkMachine visionComputer visionMotion planningSet (abstract data type)Human–computer interaction

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