Inferring guidance information in cooperative human-robot tasks

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Berger E, Vogt D, Haji Ghassemi N, Jung B, Ben Amor H
Publication year: 2013
Conference Proceedings Title: Inferring guidance information in cooperative human-robot tasks


Abstract


In many cooperative tasks between a human and a robotic assistant, the human guides the robot by exerting forces, either through direct physical interaction or indirectly via a jointly manipulated object. These physical forces perturb the robot's behavior execution and need to be compensated for in order to successfully complete such tasks. Typically, this problem is tackled by means of special purpose force sensors which are, however, not available on many robotic platforms. In contrast, we propose a machine learning approach based on sensor data, such as accelerometer and pressure sensor information. In the training phase, a statistical model of behavior execution is learned that combines Gaussian Process Regression with a novel periodic kernel. During behavior execution, predictions from the statistical model are continuously compared with stability parameters derived from current sensor readings. Differences between predicted and measured values exceeding the variance of the statistical model are interpreted as guidance information and used to adapt the robot's behavior. Several examples of cooperative tasks between a human and a humanoid NAO robot demonstrate the feasibility of our approach.



FAU Authors / FAU Editors

Haji Ghassemi, Nooshin
Lehrstuhl für Informatik 5 (Mustererkennung)


How to cite

APA:
Berger, E., Vogt, D., Haji Ghassemi, N., Jung, B., & Ben Amor, H. (2013). Inferring guidance information in cooperative human-robot tasks. In Inferring guidance information in cooperative human-robot tasks.

MLA:
Berger, Erik, et al. "Inferring guidance information in cooperative human-robot tasks." Proceedings of the Humanoid Robots (Humanoids), 2013 13th IEEE-RAS International Conference on 2013.

BibTeX: 

Last updated on 2018-08-08 at 06:04