Efficient Time-To-Collision Estimation for a Braking Supervision System with LIDAR

A system for efficiently calculating the risk of the mobile system colliding with a static obstacle, estimating the resulting time to collision and augmenting the user-commanded velocity commands is presented in this paper. The innovation of the approach is in merger of the laser range finder sensor measurements with the motion model of the mobile system and predicting the virtual path of the obstacles in the local coordinate system of the sensor. The resulting trajectories are then geometrically evaluated and intersections with the line-based mobile system outline are detected - approach avoids discretization of either temporal or spatial prediction horizons and produces the time-to-collision estimates with an analytical method. This not only improves the accuracy of the results, but also reduces the computational and storage loads of the processing system. The paper also presents a collision prevention system for a mobile system that is controlled by the human operator, allowing safe operation either for remote operation or use by the untrained/unreliable operator. The system was implemented on a rehabilitation mobile platform and preliminary results are provided and evaluated. In summary, the results show that the method is promising and easily applicable to target mobile systems.