Polyhedral Friction Cone Estimator for Object Manipulation

A polyhedral friction cone is a set of reaction wrenches that an object can experience whilst in contact with its environment. This polyhedron is a powerful tool to control an object's motion and interaction with the environment. It can be derived analytically, upon knowledge of object and environment geometries, contact point locations and friction coefficients. We propose to estimate the polyhedral friction cone so that a priori knowledge of these quantities is no longer required. Additionally, we introduce a solution to transform the estimated friction cone to avoid re-estimation while the object moves. We present an analysis of the estimated polyhedral friction cone and demonstrate its application for manipulating an object in simulation and with a real robot.

[1]  Danica Kragic,et al.  In-hand manipulation using gravity and controlled slip , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[2]  Alberto Rodriguez,et al.  Planar in-hand manipulation via motion cones , 2019, Int. J. Robotics Res..

[3]  Danica Kragic,et al.  Dexterous Manipulation Graphs , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[4]  Matthew T. Mason.  Two graphical methods for planar contact problems , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[5]  Alberto Rodriguez,et al.  A Global Quasi-Dynamic Model for Contact-Trajectory Optimization in Manipulation , 2020, Robotics: Science and Systems.

[6]  Werner Friedl,et al.  A Bin-Picking Benchmark for Systematic Evaluation of Robotic Pick-and-Place Systems , 2020, IEEE Robotics and Automation Letters.

[7]  Siddhartha S. Srinivasa,et al.  Extrinsic dexterity: In-hand manipulation with external forces , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[8]  Darwin G. Caldwell,et al.  Application of Wrench-Based Feasibility Analysis to the Online Trajectory Optimization of Legged Robots , 2017, IEEE Robotics and Automation Letters.

[9]  Jian Shi,et al.  Dynamic in-hand sliding manipulation , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[10]  Xianyi Cheng,et al.  Efficient Contact Mode Enumeration in 3D , 2021, WAFR.

[11]  Michael A. Erdmann.  A configuration space friction cone , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[12]  Oliver Brock,et al.  Exploitation of environmental constraints in human and robotic grasping , 2015, Int. J. Robotics Res..

[13]  Miomir Vukobratovic,et al.  Zero-Moment Point - Thirty Five Years of its Life , 2004, Int. J. Humanoid Robotics.

[14]  Hongkai Dai,et al.  Robust multi-contact dynamical motion planning using contact wrench set , 2016 .

[15]  Danica Kragic,et al.  Analytic grasp success prediction with tactile feedback , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[16]  Matthew T. Mason,et al.  Fast Planning for 3D Any-Pose-Reorienting Using Pivoting , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[17]  Silvia Cruciani,et al.  In-hand manipulation using three-stages open loop pivoting , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[18]  Matthew T. Mason,et al.  Manipulation with Shared Grasping , 2020, Robotics: Science and Systems.

[19]  Matthew T. Mason,et al.  Robust Execution of Contact-Rich Motion Plans by Hybrid Force-Velocity Control , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[20]  Or Tslil,et al.  Robotic Swing-Up Regrasping Manipulation Based on the Impulse–Momentum Approach and cLQR Control , 2016, IEEE Transactions on Robotics.

[21]  Shinichi Hirai,et al.  Kinematics and Statics of Manipulation Using the Theory of Polyhedral Convex Cones , 1993, Int. J. Robotics Res..

[22]  Graham E. Deacon,et al.  Accomplishing task-invariant assembly strategies by means of an inherently accommodating robot arm , 1997 .

[23]  Michael A. Erdmann,et al.  On a Representation of Friction in Configuration Space , 1994, Int. J. Robotics Res..

[24]  Jian Shi,et al.  Dynamic In-Hand Sliding Manipulation , 2017, IEEE Trans. Robotics.

[25]  Danica Kragic,et al.  Reinforcement Learning for Pivoting Task , 2017, ArXiv.

[26]  Matthew T. Mason,et al.  Mechanics and Planning of Manipulator Pushing Operations , 1986 .