Quadrotor Motion Planning in Stochastic Wind Fields

    •  Greiff, M., Vinod, A.P., Nabi, S., Cairano, S., "Quadrotor Motion Planning in Stochastic Wind Fields", American Control Conference (ACC), May 2023, pp. 4619 - 4625.
      BibTeX TR2023-056 PDF
      • @inproceedings{Greiff2023may,
      • author = {Greiff, Marcus and Vinod, Abraham P. and Nabi, Saleh and Cairano, Stefano},
      • title = {Quadrotor Motion Planning in Stochastic Wind Fields},
      • booktitle = {American Control Conference (ACC)},
      • year = 2023,
      • pages = {4619 -- 4625},
      • month = may,
      • url = {}
      • }
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  • Research Areas:

    Control, Dynamical Systems, Optimization, Robotics


In this paper, we propose a motion planner for quadrotors in windy environments. We extend a well-known convex polynomial optimization (CPO) method to incorporate known stochastic input uncertainties. In particular, we focus on a quadrotor unmanned aerial vehicle (UAV), and propose a new objective for direct minimization of the squared L2- norm of the UAV thrust, ‖f ‖2 L2 . We show that the first two moments of ‖f ‖2 L2 are convex in the optimization variables of the CPO problem, and can be minimized directly. Furthermore, we demonstrate that a constrained CPO approach can be used in this setting, contrary to the more popular unconstrained approaches. We provide examples demonstrating: (i) that inclusion of wind can yield significant improvements in the considered cost; (ii) that re-planning of complex paths at can be done at rates exceeding 100 Hz; and (iii) that the proposed method facilitates online re-planning leveraging wind in free- space defined as the union of convex sets.