Object manipulation through contact configuration regulation: multiple and intermittent contacts (2310.00798v1)
Abstract: In this work, we build on our method for manipulating unknown objects via contact configuration regulation: the estimation and control of the location, geometry, and mode of all contacts between the robot, object, and environment. We further develop our estimator and controller to enable manipulation through more complex contact interactions, including intermittent contact between the robot/object, and multiple contacts between the object/environment. In addition, we support a larger set of contact geometries at each interface. This is accomplished through a factor graph based estimation framework that reasons about the complementary kinematic and wrench constraints of contact to predict the current contact configuration. We are aided by the incorporation of a limited amount of visual feedback; which when combined with the available F/T sensing and robot proprioception, allows us to differentiate contact modes that were previously indistinguishable. We implement this revamped framework on our manipulation platform, and demonstrate that it allows the robot to perform a wider set of manipulation tasks. This includes, using a wall as a support to re-orient an object, or regulating the contact geometry between the object and the ground. Finally, we conduct ablation studies to understand the contributions from visual and tactile feedback in our manipulation framework. Our code can be found at: https://github.com/mcubelab/pbal.
- N. Doshi, O. Taylor, and A. Rodriguez, “Manipulation of unknown objects via contact configuration regulation,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2022, pp. 2693–2699.
- T. Furukawa, D. Rye, M. Dissanayake, and A. Barratt, “Automated polishing of an unknown three-dimensional surface,” Robotics and Computer-Integrated Manufacturing, vol. 12, no. 3, pp. 261–270, 1996.
- M. G. Her and H. Kazerooni, “Automated robotic deburring of parts using compliance control,” Journal of Dynamic Systems, Measurement, and Control, vol. 113, no. 1, pp. 60–66, 03 1991.
- Y. Karayiannidis, C. Smith, F. E. Vina, P. Ögren, and D. Kragic, “Model-free robot manipulation of doors and drawers by means of fixed-grasps,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2013, pp. 4485–4492.
- G. Niemeyer and J.-J. Slotine, “A simple strategy for opening an unknown door,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA), vol. 2, 1997, pp. 1448–1453.
- F. R. Hogan and A. Rodriguez, “Reactive planar non-prehensile manipulation with hybrid model predictive control,” The International Journal of Robotics Research, vol. 39, no. 7, pp. 755–773, 2020.
- Y. Hou, Z. Jia, and M. Mason, “Manipulation with Shared Grasping,” in Proceedings of Robotics: Science and Systems, Corvalis, Oregon, USA, July 2020.
- F. R. Hogan, J. Ballester, S. Dong, and A. Rodriguez, “Tactile dexterity: Manipulation primitives with tactile feedback,” in Proceedings of International Conference on Robotics and Automation (ICRA), 2020.
- D. Ma, S. Dong, and A. Rodriguez, “Extrinsic contact sensing with relative-motion tracking from distributed tactile measurements,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2021.
- Y. Shirai, D. K. Jha, A. U. Raghunathan, and D. Hong, “Tactile tool manipulation,” in arXiv preprint, 2023.
- T. Lefebvre, H. Bruyninckx, and J. D. Schutter, “Polyhedral contact formation modeling and identification for autonomous compliant motion,” IEEE Transactions on Robotics and Automation, vol. 19, no. 1, pp. 26–41, 2003.
- J. De Schutter, T. De Laet, J. Rutgeerts, W. Decré, R. Smits, E. Aertbeliën, K. Claes, and H. Bruyninckx, “Constraint-based task specification and estimation for sensor-based robot systems in the presence of geometric uncertainty,” The International Journal of Robotics Research, vol. 26, no. 5, pp. 433–455, 2007.
- Y. She, S. Wang, S. Dong, N. Sunil, A. Rodriguez, and E. Adelson, “Cable manipulation with a tactile-reactive gripper,” The International Journal of Robotics Research, 2021.
- S. Dong, D. K. Jha, D. Romeres, S. Kim, D. Nikovski, and A. Rodriguez, “Tactile-rl for insertion: Generalization to objects of unknown geometry,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2021.
- J. Liang, X. Cheng, and O. Kroemer, “Learning preconditions of hybrid force-velocity controllers for contact-rich manipulation,” in arXiv preprint, 2022.
- A. Bicchi, J. K. Salisbury, and D. L. Brock, “Contact sensing from force measurements,” The International Journal of Robotics Research, vol. 12, no. 3, pp. 249–262, 1993.
- L. Manuelli and R. Tedrake, “Localizing external contact using proprioceptive sensors: The contact particle filter,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016.
- K.-T. Yu and A. Rodriguez, “Realtime state estimation with tactile and visual sensing for inserting a suction-held object,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
- S. Wang, A. Bhatia, M. T. Mason, and A. M. Johnson, “Contact localization using velocity constraints,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
- A. Petrovskaya and O. Khatib, “Global localization of objects via touch,” IEEE Transactions on Robotics, vol. 27, no. 3, pp. 569–585, 2011.
- J. Bimbo, L. D. Seneviratne, K. Althoefer, and H. Liu, “Combining touch and vision for the estimation of an object’s pose during manipulation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2013, pp. 4021–4026.
- P. Hebert, N. Hudson, J. Ma, and J. Burdick, “Fusion of stereo vision, force-torque, and joint sensors for estimation of in-hand object location,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2011, pp. 5935–5941.
- M. C. Koval, N. S. Pollard, and S. S. Srinivasa, “Pose estimation for planar contact manipulation with manifold particle filters,” The International Journal of Robotics Research, vol. 34, no. 7, pp. 922–945, 2015.
- S. Li, S. Lyu, and J. Trinkle, “State estimation for dynamic systems with intermittent contact,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2015, pp. 3709–3715.
- W. Meeussen, J. Rutgeerts, K. Gadeyne, H. Bruyninckx, and J. D. Schutter, “Particle filters for hybrid event sensor fusion with 3d vision and force,” in Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. IEEE, 2006, pp. 518–523.
- M. Erdmann, “On a representation of friction in configuration space,” The International Journal of Robotics Research, vol. 13, no. 3, pp. 240–271, 1994.
- T. Yoshikawa and M. Kurisu, “Identification of the center of friction from pushing an object by a mobile robot,” in Proceedings of IEEE/RSJ International Workshop on Intelligent Robots and Systems (IROS), 1991.
- K. M. Lynch, “Estimating the friction parameters of pushed objects,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1993.
- J. Zhou, M. T. Mason, R. Paolini, and D. Bagnell, “A convex polynomial model for planar sliding mechanics: theory, application, and experimental validation,” The International Journal of Robotics Research, vol. 37, no. 2-3, pp. 249–265, 2018.
- S. Goyal, A. Ruina, and J. Papadopoulos, “Planar sliding with dry friction part 1. limit surface and moment function,” Wear, vol. 143, no. 2, pp. 307–330, 1991.
- C. Strub, F. Wörgötter, H. Ritter, and Y. Sandamirskaya, “Using haptics to extract object shape from rotational manipulations,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2014, pp. 2179–2186.
- S. Suresh, M. Bauza, K.-T. Yu, J. G. Mangelson, A. Rodriguez, and M. Kaess, “Tactile slam: Real-time inference of shape and pose from planar pushing,” in IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021, pp. 11 322–11 328.
- K. Yu and A. Rodriguez, “Realtime state estimation with tactile and visual sensing. application to planar manipulation,” in IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018, pp. 7778–7785.
- M. Kaess, H. Johannsson, R. Roberts, V. Ila, J. J. Leonard, and F. Dellaert, “isam2: Incremental smoothing and mapping using the bayes tree,” The International Journal of Robotics Research, vol. 31, no. 2, pp. 216–235, 2012.
- F. Dellaert and G. Contributors, “borglab/gtsam,” May 2022. [Online]. Available: https://github.com/borglab/gtsam
- D. Ma, S. Dong, and A. Rodriguez, “Extrinsic contact sensing with relative-motion tracking from distributed tactile measurements,” in IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021, pp. 11 262–11 268.