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An Analytical Continuous-Curvature Path-Smoothing Algorithm


Abstract:

An efficient and analytical continuous-curvature path-smoothing algorithm, which fits an ordered sequence of waypoints generated by an obstacle-avoidance path planner, is...Show More

Abstract:

An efficient and analytical continuous-curvature path-smoothing algorithm, which fits an ordered sequence of waypoints generated by an obstacle-avoidance path planner, is proposed. The algorithm is based upon parametric cubic Bézier curves; thus, it is inherently closed-form in its expression, and the algorithm only requires the maximum curvature to be defined. The algorithm is, thus, computational efficient and easy to implement. Results show the effectiveness of the analytical algorithm in generating a continuous-curvature path, which satisfies an upper bound-curvature constraint, and that the path generated requires less control effort to track and minimizes control-input variability.
Published in: IEEE Transactions on Robotics ( Volume: 26, Issue: 3, June 2010)
Page(s): 561 - 568
Date of Publication: 11 March 2010

ISSN Information:

Australian Centre of Field Robotics, University of Sydney, Sydney, NSW, Australia
Australian Centre of Field Robotics, University of Sydney, Sydney, NSW, Australia

I. Introduction

Nonholonomic motion planning in an obstacle-strewed environment is a difficult problem because the planner must simultaneously consider collision avoidance and nonholonomic constraints. Typical approaches involve generating a piecewise linear obstacle-free path using techniques such as A∗, Voronoi diagrams, and probabilistic roadmaps [1]–[3] and then applying a secondary-smoothing algorithm over this linear path in order to generate a continuous path for the vehicle to follow.

Australian Centre of Field Robotics, University of Sydney, Sydney, NSW, Australia
Australian Centre of Field Robotics, University of Sydney, Sydney, NSW, Australia
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References

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