Model-based Multiple Object Tracking Using Capacitive Proximity Sensors
Published in IROS 2019 Workshop, 2019
In this work, an object tracking method on capac-itive proximity sensor is presented. Arranged as a vector and installed in the sidewalls of a work table with a robot, these sensors are able to detect proximity events in the near field of the workspace, including human approaching the table or interacting with the robot. Considering the low spatial resolution of the sensors, a preprocessing method was implementedand the data for tracking was prepared. The tracking method is based on a Kalman-Filter, where the data association and occlusion problem are discussed.