Mixed initiative controller for simultaneous intervention, a model predictive control formulation

Chengsi Shang, Hao Fang, Tao Cai, Chen Chen, Wenjie Chen, Chu Wu

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Abstract

In this paper, we discussed the simultaneous intervention problem that arises from human-robot teams. The problem concerns with the case that one human operator has to intervene with several robots at almost the same time and it cannot be handled properly by existing methods. A model predictive control(MPC) based mixed initiative controller was proposed to solve this problem by embedding an intention model into the optimization problem. This method is in essence suitable for general MPC based mixed initiative controllers. The embedded intention model may cause the robot to deviate from its desired trajectory, for which conditions were developed to guarantee that the task completeness is not be affected. A comparison experiment was conducted and results showed that the proposed controller is more efficient and helpful in shortening the intervention time and allowing more robots to be successfully intervened in a simultaneous intervention scenario.

Original languageEnglish
Title of host publicationIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2805-2810
Number of pages6
ISBN (Electronic)9781509037629
DOIs
Publication statusPublished - 28 Nov 2016
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Korea, Republic of
Duration: 9 Oct 201614 Oct 2016

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2016-November
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Country/TerritoryKorea, Republic of
CityDaejeon
Period9/10/1614/10/16

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Shang, C., Fang, H., Cai, T., Chen, C., Chen, W., & Wu, C. (2016). Mixed initiative controller for simultaneous intervention, a model predictive control formulation. In IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2805-2810). Article 7759435 (IEEE International Conference on Intelligent Robots and Systems; Vol. 2016-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2016.7759435