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Path Planning to a Reachable State Using Minimum Control Effort Based Navigation Functions

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Abstract

The purpose of this paper is to present a new path-planning algorithm for planetary exploration rovers that will guide the vehicle safely to a reachable state. In particular, this work will make use of a special class of artificial potential functions called navigation functions which are guaranteed to be free of local minimum. The construction of the navigation functions in this work is motivated by the grid-based wavefront expansion method but differs in that the contour levels are defined in terms of the control effort of the system. Two new methods will be introduced in this paper for defining the navigation function. The first method will generate a minimum control effort path plan and the second method will be based on an inverse dynamics approach. Each of the control effort based methods will generate a path plan that will guide the rover’s approach towards an objective reachable state. Finally, a stable backstepping-like controller is implemented to track a trajectory defined along the path plan to the rover’s objective.

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Acknowledgements

The authors acknowledge support for this project provided by AFRL through award # FA9453-16-1-0058

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Correspondence to Kamesh Subbarao.

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Quillen, P., Muñoz, J. & Subbarao, K. Path Planning to a Reachable State Using Minimum Control Effort Based Navigation Functions. J Astronaut Sci 66, 554–581 (2019). https://doi.org/10.1007/s40295-019-00171-6

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