MPC Based Motion Planning For Mobile Robots Using Velocity Obstacle Paradigm

Model Predictive Control (MPC) has been increasingly adopted in robotics in recent years for several tasks including the real-time control of mobile robots. The main advantage of using the MPC is the possibility of adopting an optimal control policy under a set of constraints which can be used to enforce safety, like collision-free manoeuvres. In literature a well-known approach to ensure real-time collision avoidance for multi-agent systems is the Velocity Obstacle (VO) paradigm which considers the robot as a point-mass, neglecting its dynamic and kinematic constraints. In this paper, we propose an MPC-based motion planning solution that directly considers the dynamics and the kinematics of the mobile robots, exploiting the VO as a constraint on the configuration space of the controlled system. We evaluated the proposed solution in simulation using holonomic and non-holonomic kinematic and dynamic models.