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- W3134639508 abstract "Dexterous grasping is one of the most fundamental abilities of robots to implement various manipulation tasks. Robots should have the same ability as humans to plan various grasp types for dexterous grasping. This paper addresses the problem of the adaptability of grasp planning. A novel adaptive grasp planning framework is designed to adapt to various grasp types rather than a single one. In this framework, six commonly used grasp types are considered. The information of grasp type is extracted from visual data. Then, inspired by the opposition concept, a novel concept of pregrasping opposition is introduced as the pregrasping configuration to encode the information of the grasp type. After that, a two-stage adaptive grasp planning method is proposed, which determines the pregrasping opposition in Stage One and finds a feasible grasp configuration for object grasping in Stage Two. The pregrasping opposition is used as a waypoint for the formation of complex grasps. The effectiveness of the proposed framework was evaluated in simulation and real-world experiments. The experimental results demonstrated that the proposed framework can plan various grasp types for dexterous robotic grasping. Additionally, the use of grasp types helps to reduce the complexity of grasp planning and improve the grasp dexterity of robotic hands." @default.
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- W3134639508 date "2021-06-01" @default.
- W3134639508 modified "2023-09-23" @default.
- W3134639508 title "An adaptive planning framework for dexterous robotic grasping with grasp type detection" @default.
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- W3134639508 doi "https://doi.org/10.1016/j.robot.2021.103727" @default.
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