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Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots

Thomas Howard and Alonzo Kelly
International Journal of Robotics Research, Vol. 26, No. 2, pp. 141-166, February, 2007

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Abstract

We present an algorithm for wheeled mobile robot trajectory generation that achieves a high degree of generality and efficiency. The generality derives from numerical linearization and inversion of forward models of propulsion, suspension, and motion for any type of vehicle. Efficiency is achieved by using fast numerical optimization techniques and effective initial guesses for the vehicle controls parameters. This approach can accommodate such effects as rough terrain, vehicle dynamics, models of wheel-terrain interaction, and other effects of interest. It can accommodate boundary and internal constraints while optimizing an objective function that might, for example, involve such criteria as obstacle avoidance, cost, risk, time, or energy consumption in any combination. The algorithm is efficient enough to use in real time due to its use of nonlinear programming techniques that involve searching the space of parameterized vehicle controls. Applications of the presented methods are demonstrated for planetary rovers.

BibTeX Reference
@article{Howard–2007–9655,
title = {Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots},
author = {Thomas Howard and Alonzo Kelly},
booktitle = {International Journal of Robotics Research},
keyword = {mobile robots, trajectory generation, rough terrain, constrained optimization, optimal control, path planning},
notes = {This version was the one submitted to the International Journal of Robotics Research for publication. See their website for the final version of the paper.},
publisher = {Sage Publications},
school = {Robotics Institute, Carnegie Mellon University},
month = {February},
year = {2007},
volume = {26},
number = {2},
pages = {141-166},
address = {Pittsburgh, PA},
}
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