A markov decision process model for strategic decision making in sailboat racing

  • Authors:

  • Daniel S. Ferguson;Pantelis Elinas

  • Affiliations:

  • The University of Sydney, Australian Centre for Field Robotics, Sydney, Australia;The University of Sydney, Australian Centre for Field Robotics, Sydney, Australia

  • Venue:
  • Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
  • Year:
  • 2011

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Abstract

We consider the problem of strategic decision-making for inshore sailboat racing. This sequential decision-making problem is complicated by the yacht's dynamics which prevent it from sailing directly into the wind but allow it to sail close to the wind following a zigzag trajectory towards an upwind race marker. A skipper is faced with the problem of sailing the most direct route to this marker whilst minimizing the number of steering manoeuvres that slow down the boat. In this paper, we present a Decision Theoretic model for this decision-making process assuming a fully observable environment and uncertain boat dynamics. We develop a numerical Velocity Prediction Program (VPP) which allows us to predict the yacht's speed and direction of sail given the wind's strength and direction as well as the yacht's angle of attack with respect to the wind. We specify and solve a Markov Decision Process (MPD) using our VPP to estimate the rewards and transition probabilities. We also present a method for modelling the wind flow around landmasses allowing for the computation of strategies in realistic situations. Finally, we evaluate our approach in simulation showing that we can estimate optimal routes for different kinds of yachts and crew performance.