Jump Over Block (JOB): An Efficient Line-Of-Sight Checker for Grid/voxel Maps with Sparse Obstacles
Zhuo Yao, Wei Wang, Jiadong Zhang, Yan Wang, Jinjiang Li
Abstract
Line-Of-Sight (LOS) check plays a crucial role in collision avoidance and time comsuming, particularly in scenarios involving large-scale maps with sparse obstacles, as it necessitates a grid-by-grid state check. Specifically, LOS check consumes more than half of the computational time in any-angle path planning algorithms, such as Theta*, Visibility Graph, and RRT. To address this issue, we propose an efficient LOS checker for maps of ar- bitrary dimensions with sparse obstacles. Our approach involves a two-step process. Firstly, we partition the passable space into blocks until there is no vacancy for a minimum-sized block. When the adapted Bresenham algorithm reaches a surface of a block, it bypasses grid-by-grid traversal within the block and directly jumps to the opposing surface. This method significantly reduces the number of grids examined, resulting in higher efficiency compared to traditional LOS checks. We refer to our approach as Jump Over Block (JOB). To demonstrate the advantages of JOB, we compare its performance against traditional LOS checks using a widely recognized public dataset1. The results indicate that JOB incurs only 1/6 to 1/5 of the computational cost associated with raw LOS checks, making it a valuable tool for both researchers and prac- titioners in the field. In order to facilitate further research within the community, we have made the source code of the proposed algorithm publicly available2. We anticipate that this framework will contribute to the development of more efficient path planning algorithms and expedite various aspects of robotics that involve collision checks.