[1]黄鼎键,杨华山,江灏,等.基于激光雷达和温度传感的高温避障[J].福建工程学院学报,2023,21(03):244-248.[doi:10.3969/j.issn.1672-4348.2023.03.007]
　HUANG Dingjian,YANG Huashan,JIANG Hao,et al.High temperature obstacle avoidance based on lidar and temperature sensing[J].Journal of FuJian University of Technology,2023,21(03):244-248.[doi:10.3969/j.issn.1672-4348.2023.03.007]
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基于激光雷达和温度传感的高温避障()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第21卷
期数:
2023年03期
页码:
244-248
栏目:
出版日期:
2023-06-25

文章信息/Info

Title:
High temperature obstacle avoidance based on lidar and temperature sensing
作者:
黄鼎键; 杨华山; 江灏; 钟勇; 林铭昊
福建省汽车电子与电驱动技术重点实验室(福建工程学院机械与汽车工程学院)
Author(s):
HUANG Dingjian;  YANG Huashan;  JIANG Hao;  ZHONG Yong;  LIN Minghao
Key Laboratory for Automotive Electronics and Electric Drive of Fujian Province,Fujian University of Technology
关键词:
高温避障; Gmapping算法; 红外热像; 栅格; 路径规划
Keywords:
high temperature obstacle avoidance;  Gmapping algorithm;  infrared thermography;  grid;  path planning
分类号:
TP242
DOI:
10.3969/j.issn.1672-4348.2023.03.007
文献标志码:
A
摘要:
激光雷达不宜用于检测障碍物的温度。如果路径规划时仅使用激光雷达而忽视高温障碍物对智能车和其携带货物的热辐射作用,将会导致安全隐患。针对该问题,在常规RBPF SLAM 算法原理基础上,改进并运用提议分布和自适应重采样两种方法,融合红外热像模块检测出的环境温度信号,提出了一种在建图过程中改变高温障碍物栅格状态的方法;在所搭建的智能车高温避障导航测试场景下进行有无高温障碍物的导航避障对比实验。实验结果表明,该方法能让智能车在高温障碍物的环境中有效地规划路径并避开高温障碍物,提高了智能车导航的准确性和可靠性。
Abstract:
Lidar is not suitable for detecting the temperature of obstacles. If only lidar is used in path planning while ignoring the thermal radiation effect of high-temperature obstacles on the intelligent vehicle and its cargo, it will lead to safety hazards. To solve this problem, firstly, based on the principle of conventional RBPF SLAM algorithm, two methods of improved proposal distribution and adaptive resampling were studied and applied. Secondly, a method of changing the grid state of high-temperature obstacles in the process of mapping was proposed by fusing the ambient temperature signal detected by infrared thermal imaging module. Finally, a comparative experiment of navigation and obstacle avoidance with and without high-temperature obstacles was carried out under the built intelligent vehicle high temperature obstacle avoidance navigation test scenario. Experimental results demonstrate that this method can effectively plan the path and avoid the high-temperature obstacles in the environment where there are high-temperature objects, and improve the accuracy and reliability of the intelligent vehicle navigation.

参考文献/References:

［1］ 李德胜，孙一杰，张国良. 一种面向动态环境的多层代价地图更新算法［J］. 无线电工程，2022，52（7）：1284-1290.［2］ 郭园园，袁杰，赵克刚. 基于改进A*算法和动态窗口法的机器人路径规划［J］. 计算机工程与科学，2022，44（7）：1273-1281.［3］ ZHAO J W，LIU S Y，LI J Y. Research and implementation of autonomous navigation for mobile robots based on SLAM algorithm under ROS［J］. Sensors，2022，22（11）：4172.［4］ 郭智鑫，李明坤，蔡雁培，等. 基于热感与红外感应的火灾救援路线规划小车［J］. 计算机技术与发展，2020，30（4）：130-133，138.［5］ 王鹏程. 基于ROS的热成像巡检机器人设计［D］. 青岛：青岛大学，2021.［6］ WATANABE A，ENDO D，YAMAUCHI G，et al. Neonavigation meta-package：2-D/3-DOF seamless global-local planner for ROS—development and field test on the representative offshore oil plant［C］∥2016 IEEE International Symposium on Safety，Security，and Rescue Robotics （SSRR）. Lausanne，Switzerland: IEEE，2016：86-91.［7］ COOK Z，ZHAO L，LEE J，et al. Unmanned aerial system for first responders［C］∥2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence （URAI）. Goyang: IEEE，2015：306-310.［8］ WANG H N，NI J Y，QI Y，et al. Optimal design of laser SLAM algorithm based on RBPF improved resampling technology［C］∥2020 IEEE International Conference on Mechatronics and Automation （ICMA）. Beijing，China: IEEE，2020：1245-1250.［9］ GRISETTI G，STACHNISS C，BURGARD W. Improved techniques for grid mapping with Rao-Blackwellized particle filters［J］. IEEE Transactions on Robotics，2007，23（1）：34-46.［10］ 刘媛媛，公建宁，张萌，等. 基于单舵轮AGV的Gmapping SLAM导航算法研究［J］. 制造业自动化，2020，42（2）：128-130，139.［11］ 常清洋，郭立稳，武建国，等. 基于红外测温技术的高温热源定位实验研究［J］. 煤矿安全，2022，53（9）：100-105.

更新日期/Last Update: 2023-06-25