Vision-Based Environmental Novelty Detection on a Mobile Robot
Novelty detection is about recognising features that do not fit into the pattern of previous perceptions. It is an important survival trait for animals, and is also useful for robots. For example, a robot equipped with the ability to detect novelty can select which features of an environment to investigate and learn about.In this paper we enable a mobile robot to learn a model of an environment that the robot experiences through the images of a monochrome camera while exploring. Once the robot has learnt a model of this environment we move the robot to a new environment and ask it to detect those features of the new environment that do not fit into the model, i.e., the novel features. We describe a number of different algorithms for producing an input vector from the image that is suitable for presentation to the novelty filter, and demonstrate results using the approach that worked best.
Stephen Marsland Ulrich Nehmzow Jonathan Shapiro
Department of Computer Science University of Manchester Oxford Road Manchester M13 9PL, U.K.
国际会议
8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)
上海
英文
107-112
2001-11-14（万方平台首次上网日期，不代表论文的发表时间）