Robot navigation using convex model predictive control and approximate operating region optimization

Csaba Bali; Arthur Richards

doi:10.1109/IROS.2017.8206035

Robot navigation using convex model predictive control and approximate operating region optimization

Csaba Bali, Arthur Richards

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

3 Citations (Scopus)

Abstract

A method for real-time robot navigation with obstacle avoidance is presented. A two-stage approach is proposed: the use of online Simulated Annealing (SA) to optimize a convex operating region in configuration space is paired with Model Predictive Control (MPC) to determine a locally optimal motion plan. The method retains recursive feasibility guarantees from MPC and speed of solution of the convex optimal control problem. Meanwhile, the convexification performed by the SA enables the method to operate with unstructured environment representations, such as point clouds or line scans.

Original language	English
Title of host publication	2017 IEEE/RSJ Conference on Intelligent Robots and Systems (IROS 2017)
Subtitle of host publication	Proceedings of a meeting held 24-28 September 2017, Vancouver, British Columbia, Canada
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	2171-2176
Number of pages	6
ISBN (Electronic)	9781538626825
ISBN (Print)	9781538626832
DOIs	https://doi.org/10.1109/IROS.2017.8206035
Publication status	Published - Feb 2018
Event	Intelligent Robots and Systems - Vancouver, Canada Duration: 25 Sep 2017 → …

Publication series

Name
ISSN (Print)	2153-0866

Conference

Conference	Intelligent Robots and Systems
Abbreviated title	IROS
Country/Territory	Canada
City	Vancouver
Period	25/09/17 → …

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10.1109/IROS.2017.8206035

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Bali, C., & Richards, A. (2018). Robot navigation using convex model predictive control and approximate operating region optimization. In 2017 IEEE/RSJ Conference on Intelligent Robots and Systems (IROS 2017): Proceedings of a meeting held 24-28 September 2017, Vancouver, British Columbia, Canada (pp. 2171-2176). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IROS.2017.8206035

Bali, Csaba ; Richards, Arthur. / Robot navigation using convex model predictive control and approximate operating region optimization. 2017 IEEE/RSJ Conference on Intelligent Robots and Systems (IROS 2017): Proceedings of a meeting held 24-28 September 2017, Vancouver, British Columbia, Canada. Institute of Electrical and Electronics Engineers (IEEE), 2018. pp. 2171-2176

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title = "Robot navigation using convex model predictive control and approximate operating region optimization",

abstract = "A method for real-time robot navigation with obstacle avoidance is presented. A two-stage approach is proposed: the use of online Simulated Annealing (SA) to optimize a convex operating region in configuration space is paired with Model Predictive Control (MPC) to determine a locally optimal motion plan. The method retains recursive feasibility guarantees from MPC and speed of solution of the convex optimal control problem. Meanwhile, the convexification performed by the SA enables the method to operate with unstructured environment representations, such as point clouds or line scans.",

author = "Csaba Bali and Arthur Richards",

year = "2018",

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doi = "10.1109/IROS.2017.8206035",

language = "English",

isbn = "9781538626832",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "2171--2176",

booktitle = "2017 IEEE/RSJ Conference on Intelligent Robots and Systems (IROS 2017)",

address = "United States",

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Bali, C & Richards, A 2018, Robot navigation using convex model predictive control and approximate operating region optimization. in 2017 IEEE/RSJ Conference on Intelligent Robots and Systems (IROS 2017): Proceedings of a meeting held 24-28 September 2017, Vancouver, British Columbia, Canada. Institute of Electrical and Electronics Engineers (IEEE), pp. 2171-2176, Intelligent Robots and Systems, Vancouver, Canada, 25/09/17. https://doi.org/10.1109/IROS.2017.8206035

Robot navigation using convex model predictive control and approximate operating region optimization. / Bali, Csaba; Richards, Arthur.

2017 IEEE/RSJ Conference on Intelligent Robots and Systems (IROS 2017): Proceedings of a meeting held 24-28 September 2017, Vancouver, British Columbia, Canada. Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 2171-2176.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AB - A method for real-time robot navigation with obstacle avoidance is presented. A two-stage approach is proposed: the use of online Simulated Annealing (SA) to optimize a convex operating region in configuration space is paired with Model Predictive Control (MPC) to determine a locally optimal motion plan. The method retains recursive feasibility guarantees from MPC and speed of solution of the convex optimal control problem. Meanwhile, the convexification performed by the SA enables the method to operate with unstructured environment representations, such as point clouds or line scans.

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DO - 10.1109/IROS.2017.8206035

M3 - Conference Contribution (Conference Proceeding)

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Bali C, Richards A. Robot navigation using convex model predictive control and approximate operating region optimization. In 2017 IEEE/RSJ Conference on Intelligent Robots and Systems (IROS 2017): Proceedings of a meeting held 24-28 September 2017, Vancouver, British Columbia, Canada. Institute of Electrical and Electronics Engineers (IEEE). 2018. p. 2171-2176 Epub 2017 Dec 14. doi: 10.1109/IROS.2017.8206035

Robot navigation using convex model predictive control and approximate operating region optimization

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