ICRA 2011 Paper Abstract


Paper ThP212.2

Nyga, Daniel (Technische Universität München), Tenorth, Moritz (TU München), Beetz, Michael (Technische Universität München)

How-Models of Human Reaching Movements in the Context of Everyday Manipulation Activities

Scheduled for presentation during the Regular Sessions "Learning and Adaptive Systems IV" (ThP212), Thursday, May 12, 2011, 15:40−15:55, Room 5H

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on August 19, 2019

Keywords AI Reasoning Methods, Learning and Adaptive Systems, Motion and Path Planning


We present a system for learning models of human reaching trajectories in the context of everyday manipulation activities. Different kinds of trajectories are automatically discovered, and each of them is described by its semantic context. In a first step, the system clusters trajectories in observations of human everyday activities based on their shapes, and then learns the relation between these trajectories and the contexts in which they are used. The resulting models can be used for robots to select a trajectory to use in a given context. They can also serve as powerful prediction models for human motions to improve human-robot interaction. Experiments on the TUM kitchen data set show that the method is capable of discovering meaningful clusters in real-world observations of everyday activities like setting a table.



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