Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89320
Title: Perception-Link Behavior Model: Supporting a Novel Operator Interface for a Customizable Anthropomorphic Telepresence Robot
Authors: Gu, William
Seet, Gerald
Magnenat-Thalmanna, Nadia
Keywords: Unsupervised Modeling
Gesture Synthesis
Issue Date: 2017
Source: Gu, W., Seet, G., & Magnenat-Thalmanna, N. (2017). Perception-Link Behavior Model: Supporting a Novel Operator Interface for a Customizable Anthropomorphic Telepresence Robot. Robotics, 6(3), 16-.
Series/Report no.: Robotics
Abstract: A customizable anthropomorphic telepresence robot (CATR) is an emerging medium that might have the highest degree of social presence among the existing mediated communication mediums. Unfortunately, there are problems with teleoperating a CATR, and these problems can deteriorate the gesture motion in a CATR. These problems are the disruption during decoupling, discontinuity due to the unstable transmission and jerkiness due to the reactive collision avoidance. From the review, none of the existing interfaces can simultaneously fix all of the problems. Hence, a novel framework with the perception-link behavior model (PLBM) was proposed. The PLBM adopts the distributed spatiotemporal representation for all of its input signals. Equipping it with other components, the PLBM can solve the above problems with some limitations. For instance, the PLBM can retrieve missing modalities from its experience during decoupling. Next, the PLBM can handle up to a high level of drop rate in the network connection because it is dealing with gesture style and not pose. For collision prevention, the PLBM can tune the incoming gesture style so that the CATR can deliberately and smoothly avoid a collision. In summary, the framework consists of PLBM being able to increase the user’s presence on a CATR by synthesizing expressive user gestures.
URI: https://hdl.handle.net/10356/89320
http://hdl.handle.net/10220/44859
ISSN: 2218-6581
DOI: 10.3390/robotics6030016
Rights: © 2017 by The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:RRC Journal Articles

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