电力隧道消防机器人实时避障控制系统设计
|
摘要
为了解决电力隧道消防救援的难题,需要对消防机器人避障控制系统设计方法进行研究。采用当前机器人避障控制系统设计方法在电力隧道中对消防机器人进行控制时,存在响应性差和避障有效性差的问题。提出一种电力隧道消防机器人实时避障控制系统设计方法,通过电源模块、激光雷达测距模块、伺服控制模块和电机驱动电路之间相互协调合作完成消防机器人的设计,在人工势能场的原理上采用栅格法将电力隧道中的障碍物范围分为多个视窗单元格,并计算单元格中目标点和障碍物生成的吸引力和排斥力,根据计算结果得到消防机器人受到的合力,在合力的基础上对消防机器人进行控制,避开电力隧道中的障碍物,完成消防机器人在电力隧道中的避障控制。实验结果表明,所提方法的响应性高、避障有效性好。
In order to solve the difficulty of fire rescue in power tunnels, the design method of fire-fighting robot obstacle avoidance control system needs to be studied. When the current robot obstacle avoidance control system design method is used to control a fire robot in an electric tunnel, there is a problem of poor responsiveness and poor obstacle avoidance effectiveness. A design method for real-time obstacle avoidance control system for power tunnel fire fighting robots is proposed. The design of fire fighting robots is accomplished through coordination among power supply modules, laser radar distance measurement modules, servo control modules and motor drive circuits, in principle of artificial potential energy fields. The grid method is used to divide the obstacle range in the power tunnel into multiple window cells, and the attractive force and repulsive force generated by the target point and obstacle in the cell are calculated. Based on the calculation results, the resultant force of the fire robot is obtained and the resultant force is Based on the control of the fire-fighting robots, avoid obstacles in the electric tunnel, and complete the fire-fighting robot's obstacle avoidance control in the electric tunnel. The experimental results show that the proposed method has high responsiveness, good obstacle avoidance effectiveness and low energy consumption.
In order to solve the difficulty of fire rescue in power tunnels, the design method of fire-fighting robot obstacle avoidance control system needs to be studied. When the current robot obstacle avoidance control system design method is used to control a fire robot in an electric tunnel, there is a problem of poor responsiveness and poor obstacle avoidance effectiveness. A design method for real-time obstacle avoidance control system for power tunnel fire fighting robots is proposed. The design of fire fighting robots is accomplished through coordination among power supply modules, laser radar distance measurement modules, servo control modules and motor drive circuits, in principle of artificial potential energy fields. The grid method is used to divide the obstacle range in the power tunnel into multiple window cells, and the attractive force and repulsive force generated by the target point and obstacle in the cell are calculated. Based on the calculation results, the resultant force of the fire robot is obtained and the resultant force is Based on the control of the fire-fighting robots, avoid obstacles in the electric tunnel, and complete the fire-fighting robot's obstacle avoidance control in the electric tunnel. The experimental results show that the proposed method has high responsiveness, good obstacle avoidance effectiveness and low energy consumption.
引文
[1] 张海燕, 林志贤, 郭太良. 机器人避障路径规划优化控制仿真[J]. 计算机仿真, 2017, 34(9):325-330.
[2] 马小雨. 云计算环境下用于智能机器人避障的激光测距仪设计[J]. 科技通报, 2017, 33(8):110-113.
[3] 章志诚, 杜昌平. 基于激光雷达的多旋翼飞行器实时避障系统[J]. 计算机测量与控制, 2016, 24(9):117-121.
[4] 张智, 邹盛涛, 董然,等. 复杂环境建模与机器人避障规划研究[J]. 哈尔滨工程大学学报, 2016, 37(10):1373-1380.
[5] 贾松敏, 白聪轩, 王丽佳,等. 多特征分块匹配的移动机器人目标跟踪[J]. 电子设计工程, 2016(1):23-25.
[6] 徐飞. 基于改进人工势场法的机器人避障及路径规划研究[J]. 计算机科学, 2016, 43(12):293-296.
[7] 于乃功, 郑宇凌, 徐丽,等. 基于光流的非结构化环境中移动机器人避障方法[J]. 北京工业大学学报, 2017, 43(1):65-69.
[8] 卢振利, 谢亚飞, 刘超,等. 基于幅值调整法的蛇形机器人避障研究[J]. 高技术通讯, 2016, 269(8):761-766.
[9] 王学武, 严益鑫, 丁冬雁,等. 基于Lévy-PSO算法的焊接机器人避障路径规划[J]. 上海交通大学学报, 2016, 50(10):1517-1520.
[10] 马西良, 朱华. 对瓦斯分布区域避障的煤矿机器人路径规划方法[J]. 煤炭工程, 2016, 48(7):107-110.
[2] 马小雨. 云计算环境下用于智能机器人避障的激光测距仪设计[J]. 科技通报, 2017, 33(8):110-113.
[3] 章志诚, 杜昌平. 基于激光雷达的多旋翼飞行器实时避障系统[J]. 计算机测量与控制, 2016, 24(9):117-121.
[4] 张智, 邹盛涛, 董然,等. 复杂环境建模与机器人避障规划研究[J]. 哈尔滨工程大学学报, 2016, 37(10):1373-1380.
[5] 贾松敏, 白聪轩, 王丽佳,等. 多特征分块匹配的移动机器人目标跟踪[J]. 电子设计工程, 2016(1):23-25.
[6] 徐飞. 基于改进人工势场法的机器人避障及路径规划研究[J]. 计算机科学, 2016, 43(12):293-296.
[7] 于乃功, 郑宇凌, 徐丽,等. 基于光流的非结构化环境中移动机器人避障方法[J]. 北京工业大学学报, 2017, 43(1):65-69.
[8] 卢振利, 谢亚飞, 刘超,等. 基于幅值调整法的蛇形机器人避障研究[J]. 高技术通讯, 2016, 269(8):761-766.
[9] 王学武, 严益鑫, 丁冬雁,等. 基于Lévy-PSO算法的焊接机器人避障路径规划[J]. 上海交通大学学报, 2016, 50(10):1517-1520.
[10] 马西良, 朱华. 对瓦斯分布区域避障的煤矿机器人路径规划方法[J]. 煤炭工程, 2016, 48(7):107-110.