Position tracking and recognition of everyday objects by using sensors embedded in an environment and mounted on mobile robots

Abstract

This paper describes an object tracking system for a robot working in an everyday environment, which tracks and recognizes everyday objects. Passive RFID (Radio Frequency IDentification) tags are attached to the objects for object recognition. The system consists of static sensors embedded in the environment and mobile sensors mounted on mobile robots. By utilizing the different characteristics and advantages of these sensors, the system achieves good performance in an everyday environment. Although the tag ID and the position of an object carried by a person is not measurable by static sensors or by mobile sensors, the system can estimate them by using an SIR (Sequential importance resampling) particle filter that integrates the data obtained by the static sensors and the mobile sensors. In the experiment, the system successfully tracked 20 objects, some of which were held by a person.