Object search by manipulation

We investigate the problem of a robot searching for an object. This requires reasoning about both perception and manipulation: certain objects are moved because the target may be hidden behind them and others are moved because they block the manipulator's access to other objects. We contribute a formulation of the object search by manipulation problem using visibility and accessibility relations between objects. We also propose a greedy algorithm and show that it is optimal under certain conditions. We propose a second algorithm which is optimal under all conditions. This algorithm takes advantage of the structure of the visibility and accessibility relations between objects to quickly generate optimal plans. Finally, we demonstrate an implementation of both algorithms on a real robot using a real object detection system.

[1]  D. C. Baird,et al.  Experimentation: An Introduction to Measurement Theory and Experiment Design , 1965 .

[2]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[3]  J. Hopcroft,et al.  Algorithm 447: efficient algorithms for graph manipulation , 1973, CACM.

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

[5]  Yong K. Hwang,et al.  Practical path planning among movable obstacles , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[6]  Yiming Ye,et al.  Where to look next in 3D object search , 1995, Proceedings of International Symposium on Computer Vision - ISCV.

[7]  Ye,et al.  Where to Look Next in 3 D Object SearchYiming , 1995 .

[8]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[9]  E. Rivlin,et al.  Practical pushing planning for rearrangement tasks , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[10]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[11]  Yiming Ye,et al.  Sensor Planning for 3D Object Search, , 1999, Comput. Vis. Image Underst..

[12]  George Cybenko,et al.  The Traveling Agent Problem , 2001, Math. Control. Signals Syst..

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

[14]  Mark H. Overmars,et al.  An Effective Framework for Path Planning Amidst Movable Obstacles , 2006, WAFR.

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

[16]  Dinesh Manocha,et al.  Path Planning among Movable Obstacles: A Probabilistically Complete Approach , 2008, WAFR.

[17]  James J. Kuffner,et al.  OpenRAVE: A Planning Architecture for Autonomous Robotics , 2008 .

[18]  Danica Kragic,et al.  Object Search and Localization for an Indoor Mobile Robot , 2009, J. Comput. Inf. Technol..

[19]  Jun Ota,et al.  Rearrangement Planning of Multiple Movable Objects by a Mobile Robot , 2009, Adv. Robotics.

[20]  Nicholas Roy,et al.  Utilizing object-object and object-scene context when planning to find things , 2009, 2009 IEEE International Conference on Robotics and Automation.

[21]  Siddhartha S. Srinivasa,et al.  MOPED: A scalable and low latency object recognition and pose estimation system , 2010, 2010 IEEE International Conference on Robotics and Automation.

[22]  John K. Tsotsos,et al.  Visual search for an object in a 3D environment using a mobile robot , 2010, Comput. Vis. Image Underst..

[23]  Joel W. Burdick,et al.  A probabilistic framework for object search with 6-DOF pose estimation , 2011, Int. J. Robotics Res..

[24]  Alejandro Sarmiento,et al.  Motion Planning Strategy for Finding an Object with a Mobile Manipulator in Three-Dimensional Environments , 2011, Adv. Robotics.

[25]  Oliver Kroemer,et al.  Maximally informative interaction learning for scene exploration , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[26]  Leslie Pack Kaelbling,et al.  Unifying perception, estimation and action for mobile manipulation via belief space planning , 2012, 2012 IEEE International Conference on Robotics and Automation.

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

[28]  Kris K. Hauser,et al.  The minimum constraint removal problem with three robotics applications , 2014, Int. J. Robotics Res..

[29]  Gaurav S. Sukhatme,et al.  Interactive Perception in Clutter , 2012, RSS 2012.

[30]  Ross A. Knepper,et al.  Herb 2.0: Lessons Learned From Developing a Mobile Manipulator for the Home , 2012, Proceedings of the IEEE.

[31]  Thorsten Joachims,et al.  Contextually guided semantic labeling and search for three-dimensional point clouds , 2013, Int. J. Robotics Res..

[32]  Leslie Pack Kaelbling,et al.  Manipulation-based active search for occluded objects , 2013, 2013 IEEE International Conference on Robotics and Automation.