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A Framework for Collision-Tolerant Optimal Trajectory Planning of Autonomous Vehicles

Mark L. Mote,J. Afman,E. Feron

Published 2016 in arXiv.org

ABSTRACT

Collision-tolerant trajectory planning is the consideration that collisions, if they are planned appropriately, enable more effective path planning for robots capable of handling them. A mixed integer programming (MIP) optimization formulation demonstrates the computational practicality of optimizing trajectories that comprise planned collisions. A damage quantification function is proposed, and the influence of damage functions constraints on the trajectory are studied in simulation. Using a simple example, an increase in performance is achieved under this schema as compared to collision-free optimal trajectories.

PUBLICATION RECORD

  • Publication year

    2016

  • Venue

    arXiv.org

  • Publication date

    2016-11-23

  • Fields of study

    Computer Science, Engineering

  • Identifiers
    arXiv 1611.07608
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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