Abstract
Though path planning methods based on rolling windows have been successfully applied to planet rover in uncertain environment, the efficiency still remains unsatisfactory due to the single-step advancement strategy. In this paper, a novel path planning approach called Rapidly-exploring Random Tree (RRT) is introduced to efficiently find local feasible paths in the region of rolling windows. The planning step-size in each rolling window can be adaptive adjusted according to the local environment it’s moving in, which is recorded by historical information perceived by the sensors. Combined with the goal-oriented heuristic strategy, the global collision-free solution path can be generated by successively connecting the local feasible paths. A number of infield experiments demonstrate the effectiveness of the proposed method.
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© 2009 Springer-Verlag Berlin Heidelberg
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Song, J., Dai, B., Cui, H., Shan, E., He, H. (2009). An Adaptive Rolling Path Planning Method for Planet Rover in Uncertain Environment. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds) Intelligent Robotics and Applications. ICIRA 2009. Lecture Notes in Computer Science(), vol 5928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10817-4_100
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DOI: https://doi.org/10.1007/978-3-642-10817-4_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10816-7
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