Abstract
The task of a trajectory planning tries to find a sequence of driving commands that connects two configurations, whereas we have to consider nonholonomic constraints, obstacles and driving costs. In this paper, we present a new approach that supports arbitrary primitive trajectories, cost functions and constraints. The vehicle’s driving capabilities are modeled by a list of supported maneuvers. For maneuvers there exist equations that map configurations to driving commands. From all possible maneuver sequences that connect start and target, we compute the optimum with a Viterbi-like approach.
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Roth, J. (2019). A Viterbi-like Approach for Trajectory Planning with Different Maneuvers. In: Strand, M., Dillmann, R., Menegatti, E., Ghidoni, S. (eds) Intelligent Autonomous Systems 15. IAS 2018. Advances in Intelligent Systems and Computing, vol 867. Springer, Cham. https://doi.org/10.1007/978-3-030-01370-7_1
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DOI: https://doi.org/10.1007/978-3-030-01370-7_1
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