Incremental hierarchical discriminating regression for indoor visual navigation

In this paper, we investigate vision-based navigation using the incremental hierarchical discriminating regression (IHDR) algorithm. Based on the learned experience, the system gradually improves its performance through online interaction with environment. The learning process is interactive and on-line. The hierarchical structure of the IHDR algorithm allows each associative recall to be completed in O(log n) time, where it is the number of cases learned. This makes real time performance possible. The IHDR learns incrementally: each learning sample is learned or rejected based on the real time response. The proposed scheme has been successfully applied to indoor navigation.