Energy-Efficient Path Planning for Solar-Powered Mobile Robots

  • Patrick A. Plonski
  • Pratap Tokekar
  • Volkan Isler
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 88)

Abstract

We explore the problem of energy-efficient, time-constrained path planning of a solar powered robot embedded in a terrestrial environment. Because of the effects of changing weather conditions, as well as sensing concerns in complex environments, a new method for solar power prediction is desired. We present a method that uses Gaussian Process regression to build a solar map in a data-driven fashion. With this map, we perform energy-optimal path planning using a dynamic programming algorithm. We validate our map construction and path planning algorithms with outdoor experiments, and perform simulations on our solar maps to determine under which conditions the weight of added solar panels is worthwhile for a mobile robot.

Keywords

Mobile Robot Covariance Function Path Planning Solar Panel Solar Power 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Patrick A. Plonski
    • 1
  • Pratap Tokekar
    • 1
  • Volkan Isler
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of MinnesotaMinneapolisUSA

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