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Multisensor System for Safer Human-Robot Interaction

Yucong Lu, Lingqi Zeng, Gary M. Bone

Year
2006
Citations
17

Abstract

The development of a system for automatically locating and tracking a human in the vicinity of a robot is described. The system consists of multiple passive infrared (PIR) sensors, two color cameras, a pair of microwave sensors and a pair of PCs for data collection, signal processing and data fusion. The cameras are treated as individual sensors rather than a stereo pair to minimize the affect of occlusion by the robot. The area around the robot is subdivided into an occupancy grid with 0.5m by 0.5m cells. A data fusion algorithm, based on Dempster-Shafer evidence theory, is used to estimate the probability of human occupancy for each cell. This information is used to estimate the human’s location. A novel concept termed a “protective cell” is introduced to further increase the human’s safety in the presence of sensor uncertainty. Experimental results are included demonstrating the system’s effectiveness.

Keywords

SAFERHuman–robot interactionComputer scienceRobotHuman–computer interactionArtificial intelligenceComputer security

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