MPC Based Motion Planning For Mobile Robots Using Velocity Obstacle Paradigm

Abstract

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.