Bimanual Interaction with Clothes. Topology, Geometry, and Policy Representations in Robots

Twardon L. Bimanual Interaction with Clothes. Topology, Geometry, and Policy Representations in Robots. Bielefeld: Universität Bielefeld; 2019.If anthropomorphic robots are to assist people with activities of daily living, they must be able to handle all kinds of everyday objects, including highly deformable ones such as garments. The present thesis begins with a detailed problem analysis of robotic interaction with and perception of clothes. We show that handling items of clothing is very challenging due to their complex dynamics and the vast number of degrees of freedom. As a result of our analysis, we obtain a topological, geometric, and functional description of garments that supports the development of reduced object and task representations. One of the key findings is that the boundary components, which typically correspond with the openings, characterize garments well, both in terms of their topology and their inherent purpose, namely dressing. We present a polygon-based and an interactive method for identifying boundary components using RGB-D vision with application to grasping. Moreover, we propose Active Boundary Component Models (ABCMs), a constraint-based framework for tracking garment openings with point clouds. It is often difficult to maintain an accurate representation of the objects involved in contact-rich interaction tasks such as dressing assistance. Therefore, our policy optimization approach to putting a knit cap on a styrofoam head avoids modeling the details of the garment and its deformations. The experimental results suggest that a heuristic performance measure that takes into account the amount of contact established between the two objects is suitable for the task

Active Boundary Component Models for Robotic Dressing Assistance

Twardon L, Ritter H. Active Boundary Component Models for Robotic Dressing Assistance. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway, NJ: IEEE; 2016: 2811-2818

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

Twardon L, Ritter H. Learning to Put On a Knit Cap in a Head-Centric Policy Space. IEEE ROBOTICS AND AUTOMATION LETTERS. 2018;3(2):764-771.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

Interaction skills for a coat-check robot. Identifying and handling the boundary components of clothes

Twardon L, Ritter H. Interaction skills for a coat-check robot. Identifying and handling the boundary components of clothes. In: 2015 IEEE International Conference on Robotics and Automation (ICRA). Piscataway, NJ: IEEE; 2015: 3682-3688

Exploiting eye-hand coordination: a novel approach to remote manipulation

Twardon L, Finke A, Ritter H. Exploiting eye-hand coordination: a novel approach to remote manipulation. Presented at the IEEE International Conference on Robots and Systems (IROS), Tokyo, Japan

Dynamic Path Planning Adopting Human Navigation Strategies for a Domestic Mobile Robot

Yuan F, Twardon L, Hanheide M. Dynamic Path Planning Adopting Human Navigation Strategies for a Domestic Mobile Robot. In: International Conference on Intelligent Robots and Systems (IROS). Taipei, Taiwan: IEEE; 2010.Mobile robots that are employed in people’s homes need to safely navigate their environment. And natural humaninhabited environments still pose significant challenges for robots despite the impressive progress that has been achieved in the field of path planning and obstacle avoidance. These challenges mostly arise from the fact that (i) the perceptual abilities of a robot are limited, thus sometimes impeding its ability to see relevant obstacles (e.g. transparent objects), and (ii) the environment is highly dynamic being populated by humans. In this contribution we are making a case for an integrated solution to these challenges that builds upon the analysis and use of implicit human knowledge in path planning and a cascade of replanning approaches. We combine state of the art path planning and obstacle avoidance algorithms with the knowledge about how humans navigate in their very own environment. The approach results in a more robust and predictable navigation ability for domestic robots as is demonstrated in a number of experimental runs

Gaze-based scene sonification for orientation in the dark

Koesling H, Twardon L, Finke A. Gaze-based scene sonification for orientation in the dark. Presented at the Fifth International Conference on Cognitive Science, Kaliningrad, Russia

Gaze-contingent audio-visual substitution for the blind and visually impaired

Twardon L, Koesling H, Finke A, Ritter H. Gaze-contingent audio-visual substitution for the blind and visually impaired. Presented at the 7th International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health) 2013, Venice, Italy