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多传感器信息融合在自主移动机器人上的应用
Alternative TitleThe Application of Multi-sensor Data Fusion Algorithm on Mobile Robotics
杨秦敏
Subtype工学硕士
Thesis Advisor原魁
2004-06-01
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword全自主移动机器人 多传感器信息融合 嵌入式 超声传感器 环境地图建模 栅格模型 入射角 幻象目标 证据理论 证据冲突量 Autonomous Mobile Robot Multi-sensor Data Fusion Embedded Ultrasonic Sensor Map-building Grid Map Incidence Angle Phantom Tar
Abstract本文主要针对在智能全自主移动机器人上应用多传感器信息融合算法进 行了深入研究。传感器系统是智能移动机器人的一个重要组成部分。本文的 研究目标就是在自主研制高性能,低成本的嵌入式多传感器数据采集系统的 基础上,应用多传感器信息融合算法,实现机器人运行环境的地图建模,从 而提高整个多传感器系统乃至整个移动机器人系统的性能价格比。本论文主 要包括以下几个方面的内容: 1. 首先,分析了目前全自主智能移动机器人上常用的传感器系统,并 结合实际应用提出了“嵌入式环境感知系统”的思想。在此基础上,研制开 发了一种面向移动机器人的嵌入式多传感器数据采集系统,实现对多路超 声、红外、PSD、方位等传感器的实时数据采集,并通过实验验证了其可靠 性和实时性。 2. 针对超声传感器在全自主移动机器人上的应用,深入分析了其工作 原理和特性,阐述了实际应用中使用超声传感器进行测距的局限性,并对其 数学模型进行了探讨。 3. 结合超声测距存在的问题,深入探讨了移动机器人环境地图建模的 相关问题。以柱状栅格地图模型作为环境表达框架,针对以往超声传感器数 学模型存在的问题提出了一种简化了的高斯模型。在此基础上,引入超声测 距中的入射角信息,提出一种RIC(Range-Incidence Combination)方法进行 环境地图建模,其在减少幻象目标和寻门(doorway-finding)方面表现出了 很好的效果。 4. 针对柱状栅格地图模型的局限性(只能用于移动机器人快速避 障),采用证据栅格模型进行环境表达,并使用证据理论进行环境地图建模 和更新。同时,将超声传感器的信息与长距离测量传感器的测量数据进行融 合,并定义了证据冲突量以表征超声信息可靠性。通过实验进行比较发现, 该方法能够很大程度上消除超声传感器幻象目标对环境地图建模的影响。
Other AbstractThe thesis does researches on multi-sensor data fusion, focusing on a specific application - autonomous mobile robotics. Multi-sensor system is one of the most important parts of an intelligent mobile robot. The goal of this thesis is to develop a high-performance, low-cost embedded multi-sensor data acquisition system, construct and maintain a map of the environment using multi-sensor data fusion algorithm on the basis of the system, and improve the ratio of performance to cost of it and the whole mobile robot. Main work and contribution of the thesis is given as follows: 1. After investigating various multi-sensor systems used in mobile robots currently, we present a concept of "embedded environment perception system". Based on it, a multi-sensor data acquisition system for mobile robots is developed successfully, which can collect data from multiple sonar sensors, infrared sensors, PSD and orientation sensor, etc. Experimental results on a real mobile robot show its reliability and real-time capability. 2. Aiming at applying sonar sensors to mobile robots, we analyze their operation principles and performance characteristics, and explain the limitation when sonar sensors are used in mobile robots. At the same time, different mathematic models are introduced. 3. Taking into account of the uncertainty of sonar sensors, we discuss the task of map-building with mobile robots. A new sonar model is given, which is a simplified Gaussian model, to construct a two-dimensional histogram grid map. Furthermore, RIC (Range-Incidence Combination) method is introduced, which fuses incidence angle information and range measurement of sonar to build map of environment. The method exhibits a good performance in solving the problem of door-finding and reducing phantom targets. 4. To overcome the limitation of the domain of application when using histogram grid map (only useful in obstacle avoidance), we propose an alternative to represent the environment-evidence grid map. Dempster-Shafer Evidence Theory is applied in map-building. Moreover, to reduce phantom targets, we fuse data from sonar sensors and long distance measuring sensors, and define Evidence Conflict Value. Comparative experimental results show that the new method can improve the performance of sonar sensors in map-building.
shelfnumXWLW769
Other Identifier769
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6759
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
杨秦敏. 多传感器信息融合在自主移动机器人上的应用[D]. 中国科学院自动化研究所. 中国科学院研究生院,2004.
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