Proposal for Navigation System Using Three-Dimensional Maps—Self-Localization Using a 3D Map and Slope Detection Using a 2D Laser Range Finder and 3D Map

IF 0.9 Q4 ROBOTICS

Journal of Robotics and Mechatronics Pub Date : 2023-12-20 DOI:10.20965/jrm.2023.p1604

Neng Chen, S. Suga, Masato Suzuki, Tomokazu Takahashi, Yasushi Mae, Yasuhiko Arai, S. Aoyagi

引用次数: 0

Abstract

Many teams participating in robotic competitions achieve localization using a 2D map plotted using adaptive Monte Carlo localization, a robot operating system (ROS) open-source software program. However, outdoor environments often include nonlevel terrain such as slopes. In the indoor environment of multilevel structures, the data representing different levels overlap on the map. These factors can lead to localization failures. To resolve this problem, we develop a software by combining HDL localization, which is an ROS open-source software, with our own program, and use it to achieve localization based on a 3D map. Furthermore, the authors observe the erroneous recognition of a slope as a forward obstacle during a competition event. To resolve this, we propose a method to correct erroneous recognition of obstacles using a 2D laser range finder and 3D map and confirm its validity in an experiment carried out on a slope on a university campus.

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关于使用三维地图的导航系统的建议--使用三维地图进行自我定位以及使用二维激光测距仪和三维地图进行斜坡探测

许多参加机器人竞赛的团队都是利用机器人操作系统（ROS）开源软件程序自适应蒙特卡洛定位绘制的二维地图实现定位的。然而，室外环境通常包括斜坡等非水平地形。在多层结构的室内环境中，代表不同楼层的数据会在地图上重叠。这些因素都可能导致定位失败。为了解决这个问题，我们将 ROS 开源软件 HDL 本地化与我们自己的程序相结合，开发了一款软件，并利用它实现了基于三维地图的本地化。此外，作者还观察到在比赛中将斜坡错误地识别为前方障碍物的情况。为了解决这个问题，我们提出了一种利用二维激光测距仪和三维地图纠正错误障碍物识别的方法，并在大学校园的一个斜坡上进行了实验，证实了这种方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Robotics and Mechatronics ROBOTICS-

CiteScore

2.20

自引率

36.40%

发文量

134

期刊介绍： First published in 1989, the Journal of Robotics and Mechatronics (JRM) has the longest publication history in the world in this field, publishing a total of over 2,000 works exclusively on robotics and mechatronics from the first number. The Journal publishes academic papers, development reports, reviews, letters, notes, and discussions. The JRM is a peer-reviewed journal in fields such as robotics, mechatronics, automation, and system integration. Its editorial board includes wellestablished researchers and engineers in the field from the world over. The scope of the journal includes any and all topics on robotics and mechatronics. As a key technology in robotics and mechatronics, it includes actuator design, motion control, sensor design, sensor fusion, sensor networks, robot vision, audition, mechanism design, robot kinematics and dynamics, mobile robot, path planning, navigation, SLAM, robot hand, manipulator, nano/micro robot, humanoid, service and home robots, universal design, middleware, human-robot interaction, human interface, networked robotics, telerobotics, ubiquitous robot, learning, and intelligence. The scope also includes applications of robotics and automation, and system integrations in the fields of manufacturing, construction, underwater, space, agriculture, sustainability, energy conservation, ecology, rescue, hazardous environments, safety and security, dependability, medical, and welfare.