Terrain-Shape-Adaptive Coverage Path Planning With Traversability Analysis

IF 3.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent & Robotic Systems Pub Date : 2024-03-07 DOI:10.1007/s10846-024-02073-8
Wenwei Qiu, Dacheng Zhou, Wenbo Hui, Afimbo Reuben Kwabena, Yubo Xing, Yi Qian, Quan Li, Huayan Pu, Yangmin Xie
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Abstract

Coverage path planning (CPP) is in great demand with applications in agriculture, mining, manufacturing, etc. Most research in this area focused on 2D CPP problems solving the coverage problem with irregular 2D maps. Comparatively, CPP on uneven terrains is not fully solved. When there are many slopy areas in the working field, it is necessary to adjust the path shape and make it adapt to the 3D terrain surface to save energy consumption. This article proposes a terrain-shape-adaptive CPP method with three significant features. First, the paths grow by themselves according to the local terrain surface shapes. Second, the growth rule utilizes the 3D terrain traversability analysis, which makes them automatically avoid entering hazardous zones. Third, the irregularly distributed paths are connected under an optimal sequence with an improved genetic algorithm. As a result, the method can provide an autonomously growing terrain-adaptive coverage path with high energy efficiency and coverage rate compared to previous research works. It is demonstrated on various maps and is proven to be robust to terrain conditions.

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利用可穿越性分析进行地形地貌自适应覆盖路径规划
覆盖路径规划(CPP)在农业、采矿业、制造业等领域的应用需求很大。该领域的大部分研究都集中在二维 CPP 问题上,以解决不规则二维地图的覆盖问题。相比之下,不平整地形上的 CPP 问题还没有完全解决。当工作区域内有许多斜坡时,有必要调整路径形状,使其适应三维地形表面,以节省能耗。本文提出的地形自适应 CPP 方法有三个显著特点。首先,路径根据当地地形表面形状自行生长。其次,生长规则利用了三维地形可穿越性分析,使其自动避免进入危险区域。第三,通过改进的遗传算法,将不规则分布的路径按照最佳顺序连接起来。因此,与之前的研究成果相比,该方法能提供自主生长的地形适应性覆盖路径,具有较高的能效和覆盖率。该方法在各种地图上进行了演示,并被证明对地形条件具有鲁棒性。
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来源期刊
Journal of Intelligent & Robotic Systems
Journal of Intelligent & Robotic Systems 工程技术-机器人学
CiteScore
7.00
自引率
9.10%
发文量
219
审稿时长
6 months
期刊介绍: The Journal of Intelligent and Robotic Systems bridges the gap between theory and practice in all areas of intelligent systems and robotics. It publishes original, peer reviewed contributions from initial concept and theory to prototyping to final product development and commercialization. On the theoretical side, the journal features papers focusing on intelligent systems engineering, distributed intelligence systems, multi-level systems, intelligent control, multi-robot systems, cooperation and coordination of unmanned vehicle systems, etc. On the application side, the journal emphasizes autonomous systems, industrial robotic systems, multi-robot systems, aerial vehicles, mobile robot platforms, underwater robots, sensors, sensor-fusion, and sensor-based control. Readers will also find papers on real applications of intelligent and robotic systems (e.g., mechatronics, manufacturing, biomedical, underwater, humanoid, mobile/legged robot and space applications, etc.).
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