Learning to Put On a Knit Cap in a Head-Centric Policy Space

Robotic manipulation of such highly deformable objects as clothes is a challenging problem. Robot-assisted dressing adds even more complexity as the garment motions must be aligned with a human body under conditions of strong and variable occlusion. As a step toward solutions for the general task, we consider the example of a dual-arm robot with attached anthropomorphic hands that learns to put a knit cap on a styrofoam head. Our approach avoids modeling the details of the garment and its deformations. Instead, we demonstrate that a head-centric policy parameterization, combined with a suitable objective function for determining the right amount of contact between the cap and the head, enables a direct policy search algorithm to find successful trajectories for this task. We also show how a toy problem that mirrors some of the task constraints can be used to efficiently structure hyperparameter search. Additionally, we suggest a point cloud based algorithm for modeling the head as an ellipsoid which is required for defining the policy space.

[1]  Helge J. Ritter,et al.  Active Boundary Component Models for robotic dressing assistance , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[2]  C. Karen Liu,et al.  Haptic simulation for robot-assisted dressing , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[3]  Helge J. Ritter,et al.  Interaction skills for a coat-check robot: Identifying and handling the boundary components of clothes , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[4]  Christian Igel,et al.  Evolution Strategies for Direct Policy Search , 2008, PPSN.

[5]  Dirk V. Arnold,et al.  Improving Evolution Strategies through Active Covariance Matrix Adaptation , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[6]  Mohan M. Trivedi,et al.  Head Pose Estimation in Computer Vision: A Survey , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Petros Koumoutsakos,et al.  Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) , 2003, Evolutionary Computation.

[8]  Carme Torras,et al.  A friction-model-based framework for Reinforcement Learning of robotic tasks in non-rigid environments , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[9]  S. Schaal.  Dynamic Movement Primitives -A Framework for Motor Control in Humans and Humanoid Robotics , 2006 .

[10]  Yaochu Jin,et al.  Surrogate-assisted evolutionary computation: Recent advances and future challenges , 2011, Swarm Evol. Comput..

[11]  Katsushi Ikeuchi,et al.  Generation of humanoid robot motions with physical constraints using hierarchical B-spline , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Luuk J. Spreeuwers,et al.  Fast and Accurate 3D Face Recognition , 2011, International Journal of Computer Vision.

[13]  Jan Peters,et al.  Reinforcement learning in robotics: A survey , 2013, Int. J. Robotics Res..

[14]  Yiannis Demiris,et al.  Iterative path optimisation for personalised dressing assistance using vision and force information , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[15]  Takamitsu Matsubara,et al.  Reinforcement learning of clothing assistance with a dual-arm robot , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[16]  Helge J. Ritter,et al.  Robot self-protection by virtual actuator fatigue: Application to tendon-driven dexterous hands during grasping , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[17]  C. Karen Liu,et al.  What does the person feel? Learning to infer applied forces during robot-assisted dressing , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[18]  D. Eberly.  Distance from a Point to an Ellipse, an Ellipsoid, or a Hyperellipsoid , 2006 .

[19]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Greg Chance,et al.  An assistive robot to support dressing - strategies for planning and error handling , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[21]  Manuela M. Veloso,et al.  Personalized Assistance for Dressing Users , 2015, ICSR.

[22]  Nishanth Koganti,et al.  Cloth dynamics modeling in latent spaces and its application to robotic clothing assistance , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[23]  C. Karen Liu,et al.  Data-driven haptic perception for robot-assisted dressing , 2016, 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).