Robot task planning with contingencies for run-time sensing

In this work, we present a general approach to task planning based on contingent planning and run-time sensing, which forms part of a robot task planning framework called KVP. Using the general-purpose PKS planner, we model information-gathering actions at plan time that have multiple possible outcomes at run time. As a result, perception and sensing arise as necessary preconditions for manipulation, rather than being hard-coded as a task itself. We demonstrate the effectiveness of our approach on two simple scenarios covering visual and force sensing, and discuss its applicability to more general tasks in automation and mobile manipulation, involving arbitrary numbers of sensors and manipulators.

[1]  Fahiem Bacchus,et al.  A Knowledge-Based Approach to Planning with Incomplete Information and Sensing , 2002, AIPS.

[2]  Faouzi Ghorbel,et al.  A simple and efficient approach for 3D mesh approximate convex decomposition , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[3]  Rachid Alami,et al.  A Hybrid Approach to Intricate Motion, Manipulation and Task Planning , 2009, Int. J. Robotics Res..

[4]  Gerd Hirzinger,et al.  Bridging the Gap between Task Planning and Path Planning , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Nils J. Nilsson,et al.  Shakey the Robot , 1984 .

[6]  Tomás Lozano-Pérez,et al.  Task-level planning of pick-and-place robot motions , 1989, Computer.

[7]  Ufuk Topcu,et al.  Towards formal synthesis of reactive controllers for dexterous robotic manipulation , 2012, 2012 IEEE International Conference on Robotics and Automation.

[8]  Maria Pateraki,et al.  Two people walk into a bar: dynamic multi-party social interaction with a robot agent , 2012, ICMI '12.

[9]  Bernhard Nebel,et al.  Integrating symbolic and geometric planning for mobile manipulation , 2009, 2009 IEEE International Workshop on Safety, Security & Rescue Robotics (SSRR 2009).

[10]  Markus Rickert,et al.  Efficient Motion Planning for Intuitive Task Execution in Modular Manipulation Systems , 2011 .

[11]  Leslie Pack Kaelbling,et al.  Hierarchical task and motion planning in the now , 2011, 2011 IEEE International Conference on Robotics and Automation.

[12]  Alois Knoll,et al.  Game solving for industrial automation and control , 2012, 2012 IEEE International Conference on Robotics and Automation.

[13]  Fahiem Bacchus,et al.  Extending the Knowledge-Based Approach to Planning with Incomplete Information and Sensing , 2004, ICAPS.

[14]  Dirk Kraft,et al.  Combining Cognitive Vision, Knowledge-Level Planning with Sensing, and Execution Monitoring for Effective Robot Control , 2009 .

[15]  Richard Fikes,et al.  STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.

[16]  Alois Knoll,et al.  KVP: A knowledge of volumes approach to robot task planning , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  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.