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An autonomous manipulation system based on force control and optimization

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Abstract

In this paper we present an architecture for autonomous manipulation. Our approach is based on the belief that contact interactions during manipulation should be exploited to improve dexterity and that optimizing motion plans is useful to create more robust and repeatable manipulation behaviors. We therefore propose an architecture where state of the art force/torque control and optimization-based motion planning are the core components of the system. We give a detailed description of the modules that constitute the complete system and discuss the challenges inherent to creating such a system. We present experimental results for several grasping and manipulation tasks to demonstrate the performance and robustness of our approach.

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Notes

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    A detailed 3-D scan of nine of these objects was provided to each team and for the remaining three objects each team was only informed about the class of object.

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Acknowledgments

This research was supported in part by National Science Foundation Grants ECS-0326095, IIS-0535282, IIS-1017134, CNS-0619937, IIS-0917318, CBET-0922784, EECS-0926052, CNS-0960061, the DARPA Program on Autonomous Robotic Manipulation, the Army Research Office, the Okawa Foundation, the ATR Computational Neuroscience Laboratories, and the Max-Planck-Society. The authors would also like to thank the anonymous reviewers for their constructive comments.

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Correspondence to Ludovic Righetti.

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Righetti, L., Kalakrishnan, M., Pastor, P. et al. An autonomous manipulation system based on force control and optimization. Auton Robot 36, 11–30 (2014) doi:10.1007/s10514-013-9365-9

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Keywords

  • Grasping
  • Manipulation
  • Force control
  • Optimization