Experimental Robotics 2013
pdf ·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.
@inbook{ plonski2013aenergy,
title = "Energy-Efficient Path Planning for Solar-Powered Mobile Robots",
author = {Patrick Plonski and Pratap Tokekar and Volkan Isler},
booktitle = {Experimental Robotics},
year = "2013",
doi = "10.1007/978-3-319-00065-7_48",
note = "The 13th International Symposium on Experimental Robotics",
}