煤矿消防灭火机器人系统设计

陈骋; 陈秀田; 朱明亮

doi:10.13272/j.issn.1671-251x.2021090019

煤矿消防灭火机器人系统设计

doi: 10.13272/j.issn.1671-251x.2021090019

陈骋^{1, 3,},
陈秀田²,
朱明亮^{1, 3}

1.
中煤科工集团沈阳研究院有限公司, 辽宁抚顺　113122
2.
华晋焦煤有限责任公司,山西吕梁　033000
3.
煤矿安全技术国家重点实验室, 辽宁抚顺　113122

详细信息

作者简介:
陈骋（1985-），男，辽宁锦州人，助理研究员，硕士，主要研究方向为煤矿安全相关的智能装备，E-mail：314895750@qq.com

中图分类号: TD753
计量
- 文章访问数: 781
- HTML全文浏览量: 51
- PDF下载量: 31
- 被引次数: 0
出版历程
- 收稿日期: 2021-09-06
- 修回日期: 2022-03-07
- 网络出版日期: 2022-03-05

A system design for coal mine fire-fighting robots

CHEN Cheng^{1, 3
,},
CHEN Xiutian²,
ZHU Mingliang^{1, 3}

1.
CCTEG Shenyang Research Institute Co., Ltd., Fushun 113122, China
2.
Huajin Coking Coal Co., Ltd., Lüliang 033000, China
3.
State Key Laboratory of Coal Mine Safety Technology, Fushun 113122, China

摘要

摘要: 消防灭火机器人是煤矿井下防灭火治理及灾后救援的重要装备，但目前针对煤矿井下复杂地形的机器人定位、路径规划、火灾险情识别及精准灭火等方面的研究较少。针对该问题，提出了一种煤矿消防灭火机器人系统设计方案。结合超宽带(UWB)、激光雷达技术，采用迭代最近点（ICP）算法实现机器人定位初始化；结合惯性测量装置和里程计数据，采用自适应蒙特卡洛定位（AMCL）算法实现机器人实时定位，实测定位精度达5～10 cm；通过加入寻找新目标点的容忍距离参数对A^*算法进行优化，并采用优化A^*算法实现机器人路径规划，测试结果表明，采用优化A^*算法进行路径规划用时短，规划的路径合理；通过先验知识生成着火点特征图片库，采用模板匹配方法识别险情目标，测试结果表明，机器人对动态多着火点的虚警率在10%以内，识别率达90%，满足应用要求；采用速度、位置双闭环的串级控制器实现云台俯仰轴和偏航轴角度控制，并通过云台控制将消防弹投射至险情目标，为煤矿精准灭火提供技术支持。
- 煤矿防灭火 /
- 消防灭火机器人 /
- 精准灭火 /
- 实时定位 /
- UWB /
- 路径规划 /
- 目标识别 /
- 云台控制
Abstract: Although fire-fighting robots are important devices for underground coal mines to prevent and deal with fire incidents, current research has hardly studied the approaches of robot locating, path planning, and accurate fire detection and extinguishment for complex underground coal mine topography. To fill the gap, this paper proposes a system design for underground coal mine fire-fighting robots. By combining the technologies of ultra wide band (UWB) and laser radars, the design applies the iterative closest point (ICP) and the adaptive Monte Carlo localization (AMCL) algorithms to initialize robots' position and locate robots in a real time manner, respectively. By using inertial measurement units and odometers, the design can raise the real localization accuracy up to 5-10 centimeters. By adding a distance parameter to limit the searching area, an enhanced A^* algorithm is proposed to plan paths for robots. Experiments show that the algorithm can find the suitable paths in lower time cost. The design supports a robot to detect targets using a template mapping system based on a pre-generated feature image set. It limits the false positive rate to 10% (true positive rate of 90%) and completely meets the design requirement. The design allows a robot to be equipped with a cascade controller that uses feedbacks of velocity and position to control the elevation and yaw angels of the pan-tilt-zoom (PTZ). Fire extinguishing bombs can be further thrown to targets, via the PTZ, to support accurate fire extinguishment.
- coal mine fire prevention and extinguishment /
- fire-fighting robots /
- accurate fire extinguishment /
- real-time localization /
- UWB /
- path planning /
- target identification /
- pan control

HTML全文

图 1 煤矿消防灭火机器人系统结构

Figure 1. Structure of coal mine fire-fighting robot system

下载: 全尺寸图片幻灯片

图 2 AMCL算法流程

Figure 2. Flow of the AMCL algorithm

下载: 全尺寸图片幻灯片

图 3 机器人实时定位测试结果

Figure 3. Test results of robot real-time positioning

下载: 全尺寸图片幻灯片

图 4 机器人路径规划测试结果

Figure 4. Test results of robot path planning

下载: 全尺寸图片幻灯片

图 5 云台串级控制流程

Figure 5. Cascade control process of the pan-tilt-zoom (PTZ)

下载: 全尺寸图片幻灯片

表 1 路径规划指标

Table 1. Path planning indexes

序号	起止点间欧氏距离/m	算法用时/s	路径长度/m	与障碍物最小距离/m
1	5.650	1.05	10.980	0.750
2	7.095	1.25	13.813	0.900
3	6.450	1.34	13.682	0.750
4	5.732	0.78	7.433	0.640
5	8.137	1.09	11.803	0.590

下载: 导出CSV

表 2 着火点目标识别测试结果

Table 2. Test results of ignition points detection

测试场景	帧率/（帧·s⁻¹）			虚警率/%
测试场景	最大值	最小值	平均值	虚警率/%
静态单一着火点	15.1	8.2	10.5	7.9
动态单一着火点	14.7	5.0	9.3	8.2
静态多着火点	11.0	4.2	8.5	9.0
动态多着火点	9.5	3.2	5.2	9.7

下载: 导出CSV

参考文献(17)

[1]	王国法,任怀伟,赵国瑞,等. 煤矿智能化十大“痛点”解析及对策[J]. 工矿自动化,2021,47(6):1-11. WANG Guofa,REN Huaiwei,ZHAO Guorui,et al. Analysis and countermeasures of ten 'pain points' of intelligent coal mine[J]. Industry and Mine Automation,2021,47(6):1-11.
[2]	王勇,朱华,王永胜,等. 煤矿救灾机器人研究现状及需要重点解决的技术问题[J]. 煤矿机械,2007,28(4):107-109. doi: 10.3969/j.issn.1003-0794.2007.04.045 WANG Yong,ZHU Hua,WANG Yongsheng,et al. Current status and technical problems in research of coal mine rescue robot[J]. Coal Mine Machinery,2007,28(4):107-109. doi: 10.3969/j.issn.1003-0794.2007.04.045
[3]	王路明,常振兴. 机器人技术在煤矿中的应用及发展趋势[J]. 煤炭技术,2021,40(4):151-153. WANG Luming,CHANG Zhenxing. Application and development trend of robot technology in coal mine[J]. Coal Technology,2021,40(4):151-153.
[4]	杨林,马宏伟,王岩,等. 煤矿井下移动机器人运动规划方法研究[J]. 工矿自动化,2020,46(6):23-30. YANG Lin,MA Hongwei,WANG Yan,et al. Research on motion planning method of underground mobile robot[J]. Industry and Mine Automation,2020,46(6):23-30.
[5]	丁林祥. 面向家庭服务的室内移动平台设计与实现[D]. 南京: 南京理工大学, 2018. DING Linxiang. Design and implementation of a family service oriented indoor mobile platform[D]. Nanjing: Nanjing University of Science and Technology, 2018.
[6]	陈梦雯,迟克浩,陈文娟. 基于空间三角测距的激光雷达三维重建实验系统[J]. 物理实验,2019,39(3):48-53. CHEN Mengwen,CHI Kehao,CHEN Wenjuan. Laser radar 3D reconstruction experiment system based on spatial triangulation distance measurement[J]. Physics Experimentation,2019,39(3):48-53.
[7]	李波,徐月娜. 基于UWB的服务机器人室内位置感知系统[J]. 电子技术与软件工程,2018(17):90-91. LI Bo,XU Yuena. UWB-based indoor location perception system for service robot[J]. Electronic Technology & Software Engineering,2018(17):90-91.
[8]	陈志键,徐爱功,隋心,等. 室内UWB/LiDAR组合定位算法[J]. 导航定位学报,2019,7(1):38-42,111. CHEN Zhijian,XU Aigong,SUI Xin,et al. Algorithm of indoor UWB/LiDAR combined positioning[J]. Journal of Navigation and Positioning,2019,7(1):38-42,111.
[9]	GUAN R P,RISTIC B,WANG Liuping,et al. KLD sampling with Gmapping proposal for Monte Carlo localization of mobile robots[J]. Information Fusion,2019,49:79-88. doi: 10.1016/j.inffus.2018.09.003
[10]	伍阳. 利用对称性进行LiDAR点云配准[D]. 南京: 南京大学, 2016. WU Yang. Registration of LiDAR point clouds based on symmetry[D]. Nanjing: Nanjing University, 2016.
[11]	郜春艳,何秀娟,黄文美,等. 基于2-D范围扫描的室内场景识别方法[J]. 电光与控制,2018,25(12):30-34. doi: 10.3969/j.issn.1671-637X.2018.12.007 GAO Chunyan,HE Xiujuan,HUANG Wenmei,et al. An indoor scene recognition method based on 2-D range scanning[J]. Electronics Optics & Control,2018,25(12):30-34. doi: 10.3969/j.issn.1671-637X.2018.12.007
[12]	许金鹏. 移动机器人路径规划与运动控制研究[D]. 太原: 中北大学, 2018. XU Jinpeng. Research on path planning and motion control of mobile robots[D]. Taiyuan: North University of China, 2018.
[13]	董文康,陈少斌,黄宴委. 基于ROS的小车自主建图与路径规划[J]. 福建电脑,2018,34(12):100-101,112. DONG Wenkang,CHEN Shaobin,HUANG Yanwei. Autonomous mapping and path planning of cars based on ROS[J]. Fujian Computer,2018,34(12):100-101,112.
[14]	吕伟鹏. 无刷直流电机双闭环串级控制系统仿真研究[J]. 电子设计工程,2011,19(24):30-34. doi: 10.3969/j.issn.1674-6236.2011.24.010 LYU Weipeng. Research of simulation for brushless DC motor with dual closed-loop cascade control system[J]. Electronic Design Engineering,2011,19(24):30-34. doi: 10.3969/j.issn.1674-6236.2011.24.010
[15]	冯健业,赖全运,刘和顺,等. 基于云台的智能化运动目标跟踪监控系统设计[J]. 韶关学院学报,2018,39(9):52-56. doi: 10.3969/j.issn.1007-5348.2018.09.012 FENG Jianye,LAI Quanyun,LIU Heshun,et al. Design of intelligent moving target tracking and monitoring system based on pan-tilt-zoom[J]. Journal of Shaoguan University,2018,39(9):52-56. doi: 10.3969/j.issn.1007-5348.2018.09.012
[16]	沈志顺. 工业AGV载物云台稳定性控制策略研究[D]. 芜湖: 安徽工程大学, 2017. SHEN Zhishun. The stability control of industrial AGV stabilized platform[D]. Wuhu: Anhui Polytechnic University, 2017.
[17]	王继玉. ROS移动机器人跟踪系统的设计与实现[D]. 郑州: 郑州大学, 2018. WANG Jiyu. Design and implementation of ROS mobile robot tracking system[D]. Zhengzhou: Zhengzhou University, 2018.