Non-prehensile Rearrangement Planning with Learned Manipulation States and Actions

In this work we combine sampling-based motion planning with reinforcement learning and generative modeling to solve non-prehensile rearrangement problems. Our algorithm explores the composite confi ...

[1]  Rachid Alami,et al.  Two manipulation planning algorithms , 1995 .

[2]  Kostas E. Bekris,et al.  Dealing with Difficult Instances of Object Rearrangement , 2015, Robotics: Science and Systems.

[3]  Siddhartha S. Srinivasa,et al.  Robust trajectory selection for rearrangement planning as a multi-armed bandit problem , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[4]  Siddhartha S. Srinivasa,et al.  Nonprehensile whole arm rearrangement planning on physics manifolds , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[5]  Leslie Pack Kaelbling,et al.  FFRob: Leveraging symbolic planning for efficient task and motion planning , 2016, Int. J. Robotics Res..

[6]  Guy Lever,et al.  Deterministic Policy Gradient Algorithms , 2014, ICML.

[7]  Siddhartha S. Srinivasa,et al.  Rearrangement planning using object-centric and robot-centric action spaces , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[8]  Kostas E. Bekris,et al.  Rearranging similar objects with a manipulator using pebble graphs , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[9]  Siddhartha S. Srinivasa,et al.  Convergent Planning , 2016, IEEE Robotics and Automation Letters.

[10]  Thierry Siméon,et al.  Manipulation Planning with Probabilistic Roadmaps , 2004, Int. J. Robotics Res..

[11]  Leslie Pack Kaelbling,et al.  Manipulation with Multiple Action Types , 2012, ISER.

[12]  Gordon T. Wilfong,et al.  Motion planning in the presence of movable obstacles , 1988, SCG '88.

[13]  Kostas E. Bekris,et al.  Efficiently solving general rearrangement tasks: A fast extension primitive for an incremental sampling-based planner , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[14]  Leslie Pack Kaelbling,et al.  A hierarchical approach to manipulation with diverse actions , 2013, 2013 IEEE International Conference on Robotics and Automation.

[15]  Claudio Zito,et al.  Two-level RRT planning for robotic push manipulation , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  S. LaValle,et al.  Randomized Kinodynamic Planning , 2001 .

[17]  Esra Erdem,et al.  Geometric rearrangement of multiple movable objects on cluttered surfaces: A hybrid reasoning approach , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[18]  Siddhartha S. Srinivasa,et al.  Unobservable Monte Carlo planning for nonprehensile rearrangement tasks , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[19]  Tamim Asfour,et al.  Manipulation Planning Among Movable Obstacles , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[20]  Yoshua Bengio,et al.  Generative Adversarial Nets , 2014, NIPS.

[21]  Siddhartha S. Srinivasa,et al.  Kinodynamic randomized rearrangement planning via dynamic transitions between statically stable states , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[22]  Siddhartha S. Srinivasa,et al.  A Planning Framework for Non-Prehensile Manipulation under Clutter and Uncertainty , 2012, Autonomous Robots.

[23]  Oussama Khatib,et al.  MOPL: A multi-modal path planner for generic manipulation tasks , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[24]  Jun Ota,et al.  Rearrangement of multiple movable objects - integration of global and local planning methodology , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.