In this chapter, a rather straightforward procedure is presented to obtain navigation algorithms for a broad class of vehicle models, based on an adapted version of the passivity-based nonlinear MPC examined in [1]. The proposed PB/MPC approach for navigation planning can be seen as a generalization of the well-known DWA developed in [2–4]. Similar to the navigation based on the MPC/CLF [5], the PB/MPC optimization setup guarantees the task completion, which means the vehicle is being able to reach the goal position. However, whereas in the MPC/CLF navigation framework a control action that decreases the Lyapunov function has to be found in advance, which is rather difficult if not impossible for complex vehicle models, the PB/MPC navigation framework gives directly the control action as a consequence of the passivity-based control. Therefore, the PB/MPC can be easily adapted to a variety of vehicle and terrain models providing a straightforward procedure for the navigation of wide range of vehicles.


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