@book{
 title = {On heading change measurement: Improvements for any-angle path-planning},
 type = {book},
 year = {2016},
 source = {Studies in Computational Intelligence},
 identifiers = {[object Object]},
 volume = {586},
 id = {7023e400-febd-3086-aac0-8166664aab18},
 created = {2019-03-18T15:00:28.060Z},
 file_attached = {false},
 profile_id = {77ead516-4fb7-3189-a920-09efa515b9dd},
 last_modified = {2019-03-18T15:00:28.060Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© Springer International Publishing Switzerland 2016. Finding the most efficient and safe path between locations is a ubiquitous problem that occurs in smart phone GPS applications, mobile robotics and even video games. Mobile robots in particular must often operate in any type of terrain. The problem of finding the shortest path on a discretized, continuous terrain has been widely studied, and many applications have been fielded, including planetary exploration missions (i.e. the MER rovers). In this chapter we review some of the most well known path-planning algorithms and we propose a new parameter that can help us to compare them under a different measure: the heading changes and to perform some improvements in any-angle path-planning algorithms. First, we define a heuristic function to guide the process towards the objective, improving the computational cost of the search. Results show that algorithms using this heuristic get better runtime and memory usage than the former ones, with a slightly degradation of other parameters such as path length. And second, we modify an any-angle path-planning algorithm to consider heading changes during the search in order to minimize them. Experiments show that this algorithm obtains smoother paths than the other algorithms tested.},
 bibtype = {book},
 author = {Muñoz, P. and R-Moreno, M.D.}
}

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