Active sensing for human activity recognition by a home bio-monitoring robot in a home living environment

Abstract

It has been shown that mobile robots could be a potential solution to home bio-monitoring for the elderly. Through our previous studies, a mobile robot system that is able to recognize daily living activities of a target person has been developed. However, in a home environment, there are several factors of uncertainty, such as confusion with surrounding objects, occlusion by furniture, etc. Thus, the features extracted could not guarantee the correct recognition. To solve the problem, we applied active sensing strategy to the robot, especially to the body contour based behavior recognition part, by implementing 3 algorithms in a row, which enabled (1) judging irregularity of feature extraction; (2) adjusting robot viewpoints accordingly; (3) avoiding excessive viewpoint adjustment based on a short-term memory mechanism, respectively. As a result of experiment in a home living scenario, higher activity recognition accuracy was achieved by the proposed active sensing algorithms.