  There are many situations for which an unmanned ground vehicle has to work
with only partial observability of the environment. Therefore, a feasible
nonholonomic obstacle avoidance and target tracking action must be generated
immediately based on the real-time perceptual information. This paper presents
a robust approach to integrating VPH+ (enhanced vector polar histogram) and MPC
(model predictive control). VPH+ is applied to calculate the desired direction
for its environment perception ability and computational efficiency, while MPC
is explored to perform a constrained model-predictive trajectory generation.
This approach can be implemented in a reactive controller. Simulation
experiments are performed in VREP to validate the proposed approach.

Robotics