Abstract
Over the last decades, effective grasp planning algorithms, which can handle grasps of common objects for robotic hands, have been extensively investigated. Among these, synergistic actuation, a promising approach, attracts lots of attentions. However, synergies will reduce the dexterity and manipulability of robotic hands. To obtain high grasp quality, the synergy parameters need to be optimized for different objects. This paper focuses on the automatic grasp planning algorithm for synergistic underactuated hands. Our major efforts are the quantitative description of the grasp quality and the optimization of synergy parameters for different objects. Based on the proposed virtual object model, the grasp quality function, equilibrium equations and contact constraints are defined. Then an automatic grasp planning algorithm is established for synergistic underactuated hands. Finally, numerical examples are presented on a robotic hand model, and simulation results show that the proposed automatic grasp planning algorithm can be used to grasp different objects.
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Acknowledgements
This work is supported in part by the National Basic Research Program (973 Program) of China (Grant No. 2011CB013305) and the National Natural Science Foundation of China (Grant No. 51375296).
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Hua, L., Sheng, X., Lv, W., Zhu, X. (2016). Automatic Grasp Planning Algorithm for Synergistic Underactuated Hands. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9835. Springer, Cham. https://doi.org/10.1007/978-3-319-43518-3_41
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DOI: https://doi.org/10.1007/978-3-319-43518-3_41
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