Camera-based platform and sensor motion tracking for data fusion in a landmine detection system

Vehicles that serve in the role as landmine detection robots could be an important tool for demining former conflict areas. On the LOTUS platform for humanitarian demining, different sensors are used to detect a wide range of landmine types. Reliable and accurate detection depends on correctly combining the observations from the different sensors on the moving platform. Currently a method based on odometry is used to merge the readings from the sensors. In this paper a vision based approach is presented which can estimate the relative sensor pose and position together with the vehicle motion. To estimate the relative position and orientation of sensors, techniques from camera calibration are used. The platform motion is estimated from tracked features on the ground. A new approach is presented which can reduce the influence of tracking errors or other outliers on the accuracy of the ego-motion estimate. Overall, the new vision based approach for sensor localization leads to better estimates then the current odometry based method.