检测机器人在定位与路径规划中的研究综述
邓洁，张文志*，陈楷，李鑫
（内蒙古工业大学 机械工程学院，内蒙古 呼和浩特 010051）
摘要：对国内外检测机器人的研究现状进行分析，探讨了具备爬壁能力的检测机器人在总体结构、控制系统、定位方式和路径规划技术上的研究进展。定位方式方面主要简述了航迹推算定位、地图匹配定位和组合定位的原理和特点，路径规划的算法方面主要分析了全局路径规划和局部路径规划算法。重点阐述了现有检测机器人在吸附方式、定位技术和控制算法三个方面的优势和不足。经分析表明，市面上常见的检测机器人普遍存在定位准确度差和环境变化敏感度低的问题，结合检测机器人智能化和自动化的发展趋势，提出了优化扩展卡尔曼滤波方法将会对检测机器人的定位精度的提升起着重要作用，在粒子群算法上进行突破性研究将有助于检测机器人快速寻找到最优路径。基于优化扩展卡尔曼滤波方法和粒子群算法对于提升检测机器人的性能具有重要意义。
关键词：检测机器人；总体结构；定位方式；路径规划
中图分类号：TP242 文献标志码：A doi：10.3969/j.issn.1006-0316.2024.05.001
文章编号：1006-0316 (2024) 05-0001-11
Research Review of Detection Robot in Positioning and Path Planning
DENG Jie，ZHANG Wenzhi，CHEN Kai，LI Xin
( College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China )
Abstract：This paper analyzes the research status of detection robots at home and abroad, and discusses the research progress of detection robots with wall-climbing ability in the overall structure, control system, positioning mode and path planning technology. Regarding the positioning mode, the principles and characteristics of trajectory estimation positioning, map matching positioning, and integrated positioning are briefly introduced. And the path planning algorithm is analyzed with a focus on both global and local approaches. The advantages and disadvantages of the existing detection robot in adsorption mode, positioning technology and control algorithm are emphasized. The analysis shows that the common detection robots in the market generally have inadequate positioning accuracy and low sensitivity to environmental changes. In line with the development trend of intelligent and automated detection robots, it is proposed that the optimized extended Kalman filter and particle swarm optimization algorithm will play an important role in the positioning accuracy of robots, and the breakthrough in the research on particle swarm optimization will facilitate the robots in finding the optimal path quickly. The optimized extended Kalman filter and particle swarm optimization is of significant importance for enhancing the performance of detection robots.
Key words：detection robot；overall structure；positioning mode；path planning
———————————————
收稿日期：2023-08-22
基金项目：内蒙古自治区科技计划项目（2021GG0260）；内蒙古自治区自然科学基金（2020LH06003）
作者简介：邓洁（1999－），男，内蒙古赤峰人，硕士研究生，主要研究方向为机器人技术，E-mail：1917371831@qq.com。
*通讯作者：张文志（1972－），男，内蒙古呼和浩特人，博士，副教授，主要研究方向为智能机器人，E-mail：15148978512@163.com。
（内蒙古工业大学 机械工程学院，内蒙古 呼和浩特 010051）
摘要：对国内外检测机器人的研究现状进行分析，探讨了具备爬壁能力的检测机器人在总体结构、控制系统、定位方式和路径规划技术上的研究进展。定位方式方面主要简述了航迹推算定位、地图匹配定位和组合定位的原理和特点，路径规划的算法方面主要分析了全局路径规划和局部路径规划算法。重点阐述了现有检测机器人在吸附方式、定位技术和控制算法三个方面的优势和不足。经分析表明，市面上常见的检测机器人普遍存在定位准确度差和环境变化敏感度低的问题，结合检测机器人智能化和自动化的发展趋势，提出了优化扩展卡尔曼滤波方法将会对检测机器人的定位精度的提升起着重要作用，在粒子群算法上进行突破性研究将有助于检测机器人快速寻找到最优路径。基于优化扩展卡尔曼滤波方法和粒子群算法对于提升检测机器人的性能具有重要意义。
关键词：检测机器人；总体结构；定位方式；路径规划
中图分类号：TP242 文献标志码：A doi：10.3969/j.issn.1006-0316.2024.05.001
文章编号：1006-0316 (2024) 05-0001-11
Research Review of Detection Robot in Positioning and Path Planning
DENG Jie，ZHANG Wenzhi，CHEN Kai，LI Xin
( College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China )
Abstract：This paper analyzes the research status of detection robots at home and abroad, and discusses the research progress of detection robots with wall-climbing ability in the overall structure, control system, positioning mode and path planning technology. Regarding the positioning mode, the principles and characteristics of trajectory estimation positioning, map matching positioning, and integrated positioning are briefly introduced. And the path planning algorithm is analyzed with a focus on both global and local approaches. The advantages and disadvantages of the existing detection robot in adsorption mode, positioning technology and control algorithm are emphasized. The analysis shows that the common detection robots in the market generally have inadequate positioning accuracy and low sensitivity to environmental changes. In line with the development trend of intelligent and automated detection robots, it is proposed that the optimized extended Kalman filter and particle swarm optimization algorithm will play an important role in the positioning accuracy of robots, and the breakthrough in the research on particle swarm optimization will facilitate the robots in finding the optimal path quickly. The optimized extended Kalman filter and particle swarm optimization is of significant importance for enhancing the performance of detection robots.
Key words：detection robot；overall structure；positioning mode；path planning
———————————————
收稿日期：2023-08-22
基金项目：内蒙古自治区科技计划项目（2021GG0260）；内蒙古自治区自然科学基金（2020LH06003）
作者简介：邓洁（1999－），男，内蒙古赤峰人，硕士研究生，主要研究方向为机器人技术，E-mail：1917371831@qq.com。
*通讯作者：张文志（1972－），男，内蒙古呼和浩特人，博士，副教授，主要研究方向为智能机器人，E-mail：15148978512@163.com。
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