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Research at St Andrews

High Quality Goal Connection For Nonholonomic Obstacle Navigation Allowing For Drift Using Dynamic Potential Fields

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Michael Kenneth Weir, Matthew Paul Bott

School/Research organisations

Abstract

The problem we address in this paper is how to plan and execute high quality paths for robots subject to nonholonomic constraints while navigating obstacles in 2D space. The navigation is to be carried out continuously at speed and may be subject to drift that is not predictable a priori. The problem raises the challenge of adaptively maintaining a smooth robust path of low computational cost. The algorithm is complete in providing feasible paths connecting to the goal in cluttered environments without global maps or positioning while also optimising the path curvature in free space. The approach is a generic gradient-based methodology set in dynamic potential fields that are not subject to fixed local minima or other misdirecting surface features of static fields. Multiple planning and execution cycles are interleaved to allow frequent updates for dealing with unanticipated obstacles and drift. We present our methodology and demonstrate experimental results for simulated robots. The results show that low curvature paths are found that robustly connect to the goal under perturbation through a sequence of fast adaptive replanning.
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Details

Original languageEnglish
Title of host publication2010 IEEE International Conference on Robotics and Automation (ICRA)
PublisherIEEE
Pages3221-3226
Number of pages6
ISBN (Electronic)978-1-4244-5040-4
ISBN (Print)978-1-4244-5038-1
DOIs
Publication statusPublished - 2010
Event2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, United States
Duration: 3 May 20107 May 2010

Conference

Conference2010 IEEE International Conference on Robotics and Automation, ICRA 2010
CountryUnited States
CityAnchorage
Period3/05/107/05/10

    Research areas

  • dynamic potential fields, smoothness, generic, nonholonomic, motion planning, adaptive replanning, obstacle navigation, cluttered environments, local minima, mobile robots, optimality, speed, unpredictable drift, path curvature, gradient, differential drive, car-like, metric.

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  1. Enabling nonholonomic smoothness generically allowing for unpredictable drift

    Weir, M. K., Lewis, J. P. & Bott, M. P., 2008, 10th International Conference on Control, Automation, Robotics and Vision, 2008. ICARCV 2008. IEEE, p. 2072-2077 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  2. POTBUG: A mind's eye approach to providing BUG-like guarantees for adaptive obstacle navigation using dynamic potential fields

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    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. Forward Chaining for Robot and Agent Navigation using Potential Fields

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  5. An Approach to Guaranteeing Generalisation in Neural Networks

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ID: 45438824

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