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Speed Optimization for Incremental Updating of Grid-based Distance Maps

College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
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Appl. Sci. 2019, 9(10), 2029; https://doi.org/10.3390/app9102029
Received: 2 April 2019 / Revised: 10 May 2019 / Accepted: 13 May 2019 / Published: 16 May 2019
(This article belongs to the Special Issue Mobile Robots Navigation)
PDF [1532 KB, uploaded 16 May 2019]

Abstract

In the context of robotics and game AI, grid-based Distance Maps (DMs) are often used to fulfill collision checks by providing each traversable cell maximal clearance to its closest obstacle. A key challenge for DMs’ application is how to improve the efficiency of updating the distance values when cell states are changed (i.e., changes caused by newly inserted or removed obstacles). To this end, this paper presents a novel algorithm to speed up the construction of DMs on planar, eight-connected grids. The novelty of our algorithm, Canonical Ordering Dynamic Brushfire (CODB), lies in two aspects: firstly, it only updates those cells which are affected by the changes; secondly, it employs the strategy of Canonical Ordering from the fast path planning community to guide the direction of the update; therefore, the construction requires much fewer cell visits and less computation costs compared to previous algorithms. Furthermore, we propose algorithms to compute DM-based subgoal graphs. Such a spatial representation can be used to provide high-level, collision-free roadmaps for agents with certain safety radius to engage fast and rational path planning tasks. We present our algorithm both intuitively and through pseudocode, compare it to competing algorithms in simulated scenarios, and demonstrate its usefulness for real-time path planning tasks.
Keywords: distance map; incremental algorithms; canonical ordering; path planning; subgoal graph distance map; incremental algorithms; canonical ordering; path planning; subgoal graph
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Qin, L.; Hu, Y.; Yin, Q.; Zeng, J. Speed Optimization for Incremental Updating of Grid-based Distance Maps. Appl. Sci. 2019, 9, 2029.

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