Automatic position calibration and sensor displacement detection for networks of laser range finders for human tracking

Laser range finders are a non-invasive tool which can be used for anonymously tracking the motion of people and robots in real-world environments with high accuracy. Based on a commercial system we have developed, this paper addresses two practical issues of using networks of portable laser range finders in field environments. We first describe a technique for automated calibration of sensor positions and orientations, by using velocity-based matching of observed human trajectories to define constraints between the sensors. We then propose a mechanism for detecting when a sensor has been moved out of alignment, which can be used to alert an operator of the condition and automatically exclude erroneous data from tracking calculations. After describing our techniques for solving these problems, we demonstrate the effectiveness of our calibration and error detection systems in live trials with our real-time system, as well as offline tests based on scan data recorded from field trials.