The Grid-Based Path Planning Competition: 2014 Entries and Results
نویسندگان
چکیده
The Grid-Based Path Planning Competition has just completed its third iteration. The entries used in the competition have improved significantly during this time, changing the view of the state of the art of gridbased pathfinding. Furthermore, the entries from the competition have been made publicly available, improving the ability of researchers to compare their work. This paper summarizes the entries to the 2014 competition, presents the 2014 competition results, and talks about what has been learned and where there is room for improvement. Introduction and Background Grid-based path planning is a broadly studied topic, with a large variety of published approaches across many application domains. For many years work in this domain lacked broadly distributed standard benchmark problems for comparing work and standard implementations for comparing the quality of work. The first author of this paper worked to fix both of these situations by (1) introducing a variety of standard benchmark problems that can be used to test programs that run on grid-based maps and (2) by starting the grid-based path planning competition (GPPC). Citation counts suggest that the pathfinding benchmarks have been broadly adopted. (See (Sturtevant 2012) for the origin of each of the maps in the benchmark set.) The GPPC competition has run three times, in 2012, 2013, and 2014. Over this time period there has been a significant increase in the performance of entries to the competition, and the understanding of the structure of grid-based maps has also improved. This paper describes in detail the methodology used for the competition and the results from the 2014 competition. Copyright c © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Following this, the authors of each of the 2014 entries describe their entries. The paper concludes with a discussion of future directions for the competition and for grid-based pathfinding research.
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