Local obstacle avoidance method based on velocity space approach in dynamic environments

Local obstacle avoidance in dynamic environments, as a principal capability for mobile robots, plays an important role in autonomous navigation. A variety of velocity space methods such as the curvature velocity method (CVM), the lane curvature method (LCM) and the beam curvature method (BCM) formulate the local obstacle avoidance problem as one of constrained optimization in the velocity space and thus perform better than other local obstacle avoidance techniques by taking into account the physical constraints of the environment and the dynamics of the vehicle. A new local obstacle avoidance approach is presented in this paper to remedy some limitations of the traditional velocity space method. The conversion from Cartesian space to configuration space makes it possible for the proposed method to be used in unknown or partially known environments. By adding the beam width into the objective function and combining the proposed prediction model of collision with the improved BCM, not only does the method inherit the smoothness of CVM, the safety of LCM and the speediness of BCM, but also it can realize smooth, safe and speedy navigation in dynamic environments. The comparative navigation experiments executed by actual mobile robots in both static and dynamic scenes demonstrate that the proposed method is not only feasible but also valid.