A constrained VFH algorithm for motion planning of autonomous vehicles

Abstract

The Vector Field Histogram (VFH) is a classical motion planning algorithm which is widely used to handle the trajectory planning problem of mobile robots. However, the traditional VFH algorithm is rarely applied to autonomous vehicles due to the vehicle's well-known non-holonomic constraints, especially in urban environments. To address this problem, we propose a constrained VFH algorithm which takes both kinematic and dynamic constraints of the vehicle into consideration. The goal is achieved via two contributions that concern both kinematic and dynamic constraints of the vehicle. First, we develop a new active region for VFH to guarantee that all states within the region are reachable for the vehicle. Second, we improve the cost function to guide the search to favor feasible motion direction for the vehicle. The proposed algorithm is extensively tested in various simulated urban environments, and experimental results validate its efficiency.