A fast, GPU-based geometrical placement planner for unknown sensor-modelled objects and placement areas

A Personal Robot should be able to handle unknown objects in unknown environments. For a manipulation task the question what to do with an object once it had been grasped is one of the most essential ones beside the grasping task itself. Moreover, the planning time should be at least as fast as the time the robot needs for its motions. We propose a fast placement planner for sensor-modelled objects in complex environments. The planner computes a stable position and orientation for the object in the environment. The algorithm uses only geometric information, most notably no force or torque sensor is required. In particular, we introduce a novel approach regarding the pose computation. By means of experiments with various household objects the robustness and performance are validated. Further on, we compare our approach with a pose computation using a physics simulation framework.

[1]  Dominik Henrich,et al.  GPU-based Grasp And Placement Planners For Sensor-modelled Objects , 2014, ISR 2014.

[2]  Charles C. Kemp,et al.  Manipulation in Human Environments , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[3]  Dominik Henrich,et al.  Fast Vision-based Grasp and Delivery Planning for unknown Objects , 2012, ROBOTIK.

[4]  Daniele Vigo,et al.  The Three-Dimensional Bin Packing Problem , 2000, Oper. Res..

[5]  Akansel Cosgun,et al.  Push planning for object placement on cluttered table surfaces , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Xiang Song,et al.  Construction heuristics for two-dimensional irregular shape bin packing with guillotine constraints , 2013, Eur. J. Oper. Res..

[7]  Yun Jiang,et al.  Hallucinating Humans for Learning Robotic Placement of Objects , 2012, ISER.

[8]  James M. Rehg,et al.  Perceiving clutter and surfaces for object placement in indoor environments , 2010, 2010 10th IEEE-RAS International Conference on Humanoid Robots.

[9]  Yun Jiang,et al.  Learning to place new objects in a scene , 2012, Int. J. Robotics Res..

[10]  Dominik Henrich,et al.  A geometrical placement planner for unknown sensor-modelled objects and placement areas , 2013, 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[11]  Gary R. Bradski,et al.  Monte Carlo Pose Estimation with Quaternion Kernels and the Bingham Distribution , 2011, Robotics: Science and Systems.

[12]  Ramón Alvarez-Valdés,et al.  A hybrid GRASP/VND algorithm for two- and three-dimensional bin packing , 2010, Ann. Oper. Res..

[13]  E. E. Bischoff,et al.  Issues in the development of approaches to container loading , 1995 .

[14]  Tim Foley,et al.  KD-tree acceleration structures for a GPU raytracer , 2005, HWWS '05.

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

[16]  Darius Burschka,et al.  Rigid 3D geometry matching for grasping of known objects in cluttered scenes , 2012, Int. J. Robotics Res..

[17]  Kensuke Harada,et al.  Object placement planner for robotic pick and place tasks , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Daniel Leidner,et al.  Power grasp planning for anthropomorphic robot hands , 2012, 2012 IEEE International Conference on Robotics and Automation.

[19]  Anis Sahbani,et al.  An overview of 3D object grasp synthesis algorithms , 2012, Robotics Auton. Syst..

[20]  Daniel Cohen-Or,et al.  Upright orientation of man-made objects , 2008, ACM Trans. Graph..