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引用次数: 23

摘要

一个希望探索未知和动态环境的移动机器人,必须建立其环境的地图,同时确保它不会在这个过程中迷路。然而,当前基于特征的定位技术可能会变得不稳定,如果机器人以这样的方式驱动,其传感器无法识别这些特征。提出了一种新的动态路径规划方法,支持定位过程的数据采集以及在探索先验未知室内环境时提取新特征。在作者的移动机器人Roamer上的实际实验表明,在探索未知环境时,整体定位稳定性和特征提取过程显着提高。
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Sonar feature based exploration
A mobile robot wishing to explore unknown and dynamic environments, has to build up maps of its environment while at the same time ensuring that it does not become lost in the process. However current feature based localisation techniques can become unstable if the robot drives in such a way that its sensors cannot recognise these features. A novel dynamic path planning approach is presented that supports the data acquisition for the localisation process as well as the extraction of new feature while exploring an a priori unknown indoor environment. Real experiments on the authors' mobile robot Roamer have shown that the overall localisation stability and the feature extraction process were improved significantly while exploring an unknown environment.
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