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A long-standing question in robot hand design is how accurate tactile sensing must be.
Y. Chebotar, K. Hausman, Z. Su, G. S. Sukhatme, and S. Schaal, “Self-supervised regrasping using spatio-temporal tactile features and reinforcement learning,” in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2016, pp. 1960–1966
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N. Koenig and A. Howard, “Design and use paradigms for gazebo, an open-source multi-robot simulator,” in IEEE/RSJ International Conference on Intelligent Robots and Systems , Sendai, Japan, Sep 2004, pp. 2149–2154
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M. Quigley, B. Gerkey, K. Conley, J. Faust, T. Foote, J. Leibs, E. Berger, R. Wheeler, and A. Ng, “Ros: an open-source robot operating system,” in Proc. of the IEEE Intl. Conf. on Robotics and Automation (ICRA) Workshop on Open Source Robotics , Kobe, Japan, May 2009
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A. M. Dollar, L. P. Jentoft, J. H. Gao, and R. D. Howe, “Contact sensing and grasping performance of compliant hands,” Autonomous Robots , vol. 28, no. 1, pp. 65–75, 2010
2010
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J. M. Hsu and S. C. Peters, “Extending open dynamics engine for the darpa virtual robotics challenge,” in Proceedings of the 4th International Conference on Simulation, Modeling, and Programming for Autonomous Robots - Volume 8810 , ser. SIMPAR 2014. Berlin, Heidelberg: Springer-Verlag, 2014, p. 37–48
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M. A. Roa and R. Suárez, “Grasp quality measures: review and performance,” Autonomous robots , vol. 38, no. 1, pp. 65–88, 2015
2015
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T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine, “Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,” 2018
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H. Merzić, M. Bogdanović, D. Kappler, L. Righetti, and J. Bohg, “Leveraging contact forces for learning to grasp,” in 2019 International Conference on Robotics and Automation (ICRA) , 2019, pp. 3615–3621
2019
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A. Melnik, L. Lach, M. Plappert, T. Korthals, R. Haschke, and H. Ritter, “Tactile sensing and deep reinforcement learning for in-hand manipulation tasks,” in IROS Workshop on Autonomous Object Manipulation , 2019
2019
Later among the works it cites.
2019
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M. R. Cutkosky and W. Provancher, “Force and tactile sensing,” in Springer Handbook of Robotics . Springer, 2016, pp. 717–736
2016
Cited alongside, same era.
D. Prattichizzo and J. C. Trinkle, “Grasping,” in Springer Handbook of Robotics . Springer, 2016, pp. 955–988
2016
Cited alongside, same era.
J. R. Taylor, E. M. Drumwright, and J. Hsu, “Analysis of grasping failures in multi-rigid body simulations,” in 2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR) , 2016, pp. 295–301
2016
Cited alongside, same era.
Q. Wan and R. D. Howe, “Modeling the effects of contact sensor resolution on grasp success,” IEEE Robotics and Automation Letters , vol. 3, no. 3, pp. 1933–1940, 2018
2018
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J. Lee, M. X. Grey, S. Ha, T. Kunz, S. Jain, Y. Ye, S. S. Srinivasa, M. Stilman, and C. K. Liu, “Dart: Dynamic animation and robotics toolkit,” Journal of Open Source Software , vol. 3, no. 22, p. 500, 2018
2018
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A. Raffin, A. Hill, M. Ernestus, A. Gleave, A. Kanervisto, and N. Dormann, “Stable baselines3,” https://github.com/DLR-RM/stable-baselines3 , 2019
2019
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W. Hu, C. Yang, K. Yuan, and Z. Li, “Reaching, grasping and re-grasping: Learning multimode grasping skills,” 2020
2020
Later among the works it cites.
——, “Using tactile sensing to improve the sample efficiency and performance of deep deterministic policy gradients for simulated in-hand manipulation tasks,” Frontiers in Robotics and AI , vol. 8, p. 57, 2021
2021
Closest in time.
D. Silver, S. Singh, D. Precup, and R. S. Sutton, “Reward is enough,” Artificial Intelligence , vol. 299, p. 103535, 2021
2021
Closest in time.