Online motion planning over uneven terrain with walking primitives and regression

Sotiris Apostolopoulos; Marion Leibold; Martin Buss

doi:10.1109/ICRA.2016.7487568

Online motion planning over uneven terrain with walking primitives and regression

Sotiris Apostolopoulos, Marion Leibold, Martin Buss

Chair of Automatic Control Engineering

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

This paper introduces an online motion planning algorithm and a motion generation methodology for underactuated dynamic planar walking on uneven terrain. The key idea is to utilize a database of Motion Primitives and use them as training examples in a regression methodology, which is utilized when there is no match between the terrain variation and the Motion Primitives in the database. Among the key features which enable the algorithm to be suitable for real-time purposes is the proposed best first graph search approach and the small inference time of the regression methodology, which in this paper is the Gaussian Process.

Original language	English
Title of host publication	2016 IEEE International Conference on Robotics and Automation, ICRA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3799-3805
Number of pages	7
ISBN (Electronic)	9781467380263
DOIs	https://doi.org/10.1109/ICRA.2016.7487568
State	Published - 8 Jun 2016
Event	2016 IEEE International Conference on Robotics and Automation, ICRA 2016 - Stockholm, Sweden Duration: 16 May 2016 → 21 May 2016

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
Volume	2016-June
ISSN (Print)	1050-4729

Conference

Conference	2016 IEEE International Conference on Robotics and Automation, ICRA 2016
Country/Territory	Sweden
City	Stockholm
Period	16/05/16 → 21/05/16

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10.1109/ICRA.2016.7487568

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Apostolopoulos, S., Leibold, M., & Buss, M. (2016). Online motion planning over uneven terrain with walking primitives and regression. In 2016 IEEE International Conference on Robotics and Automation, ICRA 2016 (pp. 3799-3805). Article 7487568 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2016-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2016.7487568

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title = "Online motion planning over uneven terrain with walking primitives and regression",

abstract = "This paper introduces an online motion planning algorithm and a motion generation methodology for underactuated dynamic planar walking on uneven terrain. The key idea is to utilize a database of Motion Primitives and use them as training examples in a regression methodology, which is utilized when there is no match between the terrain variation and the Motion Primitives in the database. Among the key features which enable the algorithm to be suitable for real-time purposes is the proposed best first graph search approach and the small inference time of the regression methodology, which in this paper is the Gaussian Process.",

author = "Sotiris Apostolopoulos and Marion Leibold and Martin Buss",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Robotics and Automation, ICRA 2016 ; Conference date: 16-05-2016 Through 21-05-2016",

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Apostolopoulos, S, Leibold, M & Buss, M 2016, Online motion planning over uneven terrain with walking primitives and regression. in 2016 IEEE International Conference on Robotics and Automation, ICRA 2016., 7487568, Proceedings - IEEE International Conference on Robotics and Automation, vol. 2016-June, Institute of Electrical and Electronics Engineers Inc., pp. 3799-3805, 2016 IEEE International Conference on Robotics and Automation, ICRA 2016, Stockholm, Sweden, 16/05/16. https://doi.org/10.1109/ICRA.2016.7487568

Online motion planning over uneven terrain with walking primitives and regression. / Apostolopoulos, Sotiris; Leibold, Marion; Buss, Martin.
2016 IEEE International Conference on Robotics and Automation, ICRA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3799-3805 7487568 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2016-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - This paper introduces an online motion planning algorithm and a motion generation methodology for underactuated dynamic planar walking on uneven terrain. The key idea is to utilize a database of Motion Primitives and use them as training examples in a regression methodology, which is utilized when there is no match between the terrain variation and the Motion Primitives in the database. Among the key features which enable the algorithm to be suitable for real-time purposes is the proposed best first graph search approach and the small inference time of the regression methodology, which in this paper is the Gaussian Process.

AB - This paper introduces an online motion planning algorithm and a motion generation methodology for underactuated dynamic planar walking on uneven terrain. The key idea is to utilize a database of Motion Primitives and use them as training examples in a regression methodology, which is utilized when there is no match between the terrain variation and the Motion Primitives in the database. Among the key features which enable the algorithm to be suitable for real-time purposes is the proposed best first graph search approach and the small inference time of the regression methodology, which in this paper is the Gaussian Process.

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Apostolopoulos S, Leibold M, Buss M. Online motion planning over uneven terrain with walking primitives and regression. In 2016 IEEE International Conference on Robotics and Automation, ICRA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3799-3805. 7487568. (Proceedings - IEEE International Conference on Robotics and Automation). doi: 10.1109/ICRA.2016.7487568

Online motion planning over uneven terrain with walking primitives and regression

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