Utilizing parallax information for collision avoidance in dynamic environments

This paper studies an active steering problem of unmanned ground vehicles (UGVs) when avoiding obstacles during sensor based navigation in unknown environments. The overall problem is treated using the nonlinear model predictive framework, in which the sensor information of a limited sensing range is incorporated online. Results show that the introduction of the modified parallax effectively reflects the threat of obstacles and consequently achieves safe navigation in unknown environments satisfying dynamic constraints.