An Uncertainty Model of Stereo Vision and Its Application to Vision-Motion Planning of Robot

摘要

This paper describes an uncertainty model of stereo vision and its application to a visionmotion planning for a mobile robot. In general, recognition of an environment requires much computation and the recognition result includes uncertainty. In planning, therefore, a trade-off must be considered between the cost of visual recognition and the effect of information obtained by recognition. Such a trade-off must be formulated on the basis of a model of vision which describes the required time for visual processing and uncertainty of information to be obtained. In this paper, an uncertainty model of stereo vision is described, in which not only the quantization error but also false matchings of features are considered. A strategy for resolving ambiguous matchings is also proposed. Using the uncertainty model in the planner, an optimal plan for a real world problem is generated. An efficient solving strategy is also described which employs a pruning method based on the lower bound of the t...