传感器融合技术在机器人环境感知中的应用
摘 要
随着机器人技术的不断发展，其在复杂环境中的应用对环境感知能力提出了更高要求，传感器融合技术成为提升机器人环境感知性能的关键途径。本研究旨在探讨传感器融合技术在机器人环境感知中的应用，以实现更精准、全面的环境信息获取。通过分析不同类型传感器（如视觉传感器、激光雷达、超声波传感器等）的特点及其在环境感知中的优势与局限性，采用多源数据融合方法，包括基于贝叶斯理论的概率融合、卡尔曼滤化器的状态估计融合等，构建了融合多种传感器信息的机器人环境感知系统。实验结果表明，该系统能够有效提高机器人对环境的理解能力，在障碍物检测、定位导航等方面表现出色，相较于单一传感器系统，其感知精度提高了约30%，鲁棒性也显著增强。
关键词：传感器融合技术 机器人环境感知 多源数据融合
Abstract
With the continuous development of robot technology, its application in complex environments has put forward higher requirements for the environmental perception ability, and sensor fusion technology has become a key way to improve the environmental perception performance of robots. The purpose of this study is to explore the application of sensor fusion technology in robot environment perception in order to achieve more accurate and comprehensive acquisition of environmental information. Through the analysis of different types of sensors (such as visual sensor, laser radar, ultrasonic sensor, etc.) characteristics and its advantages and limitations in environmental perception, using multi-source data fusion method, including the Bayesian theory, the probability of fusion, build the fusion of a variety of sensor information robot environment perception system. The experimental results show that the system can effectively improve the robot's understanding of the environment, and perform well in obstacle detection, positioning and navigation and other aspects. Compared with a single sensor system, its perception accuracy is improved by about 30%, and its robustness is also significantly enhanced.
Keyword:Sensor Fusion Technology Robot Environmental Perception Multi-source Data Fusion
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状综述 1
1.3本文研究方法概述 2
2传感器融合技术基础理论 2
2.1传感器融合的基本概念 2
2.2常用传感器类型及其特性 3
2.3融合算法原理分析 3
3机器人环境感知需求分析 4
3.1环境感知任务分类 4
3.2不同场景下的感知要求 5
3.3感知精度与时效性考量 5
4传感器融合在机器人中的应用实践 6
4.1定位与导航中的应用 6
4.2障碍物检测与避障 7
4.3复杂环境适应能力提升 7
结论 8
参考文献 10
致谢 11
摘 要
随着机器人技术的不断发展，其在复杂环境中的应用对环境感知能力提出了更高要求，传感器融合技术成为提升机器人环境感知性能的关键途径。本研究旨在探讨传感器融合技术在机器人环境感知中的应用，以实现更精准、全面的环境信息获取。通过分析不同类型传感器（如视觉传感器、激光雷达、超声波传感器等）的特点及其在环境感知中的优势与局限性，采用多源数据融合方法，包括基于贝叶斯理论的概率融合、卡尔曼滤化器的状态估计融合等，构建了融合多种传感器信息的机器人环境感知系统。实验结果表明，该系统能够有效提高机器人对环境的理解能力，在障碍物检测、定位导航等方面表现出色，相较于单一传感器系统，其感知精度提高了约30%，鲁棒性也显著增强。
关键词：传感器融合技术 机器人环境感知 多源数据融合
Abstract
With the continuous development of robot technology, its application in complex environments has put forward higher requirements for the environmental perception ability, and sensor fusion technology has become a key way to improve the environmental perception performance of robots. The purpose of this study is to explore the application of sensor fusion technology in robot environment perception in order to achieve more accurate and comprehensive acquisition of environmental information. Through the analysis of different types of sensors (such as visual sensor, laser radar, ultrasonic sensor, etc.) characteristics and its advantages and limitations in environmental perception, using multi-source data fusion method, including the Bayesian theory, the probability of fusion, build the fusion of a variety of sensor information robot environment perception system. The experimental results show that the system can effectively improve the robot's understanding of the environment, and perform well in obstacle detection, positioning and navigation and other aspects. Compared with a single sensor system, its perception accuracy is improved by about 30%, and its robustness is also significantly enhanced.
Keyword:Sensor Fusion Technology Robot Environmental Perception Multi-source Data Fusion
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状综述 1
1.3本文研究方法概述 2
2传感器融合技术基础理论 2
2.1传感器融合的基本概念 2
2.2常用传感器类型及其特性 3
2.3融合算法原理分析 3
3机器人环境感知需求分析 4
3.1环境感知任务分类 4
3.2不同场景下的感知要求 5
3.3感知精度与时效性考量 5
4传感器融合在机器人中的应用实践 6
4.1定位与导航中的应用 6
4.2障碍物检测与避障 7
4.3复杂环境适应能力提升 7
结论 8
参考文献 10
致谢 11
