Autonomous vehicles: Path planning and control

This talk focuses on sampling-based planning and MPC-based control approaches that allow to address planning and trajectory tracking, taking into account vehicle kino-dynamics and actuation constraint

Abstract

The popularity of the research on wheeled mobile robots has been recently increasing, due to their possible use in different outdoor environments. Planetary explorations, search and rescue missions in hazardous areas, surveillance, humanitarian de-mining, drive-less mobility, as well as agriculture works represent possible applications for autonomous vehicles in natural and urban environments. Differently from the case of indoor mobile robotics, where only flat terrains are considered, outdoor robotics deals with all possible natural terrains.

The unstructured environment, terrain roughness and poorly traversable terrains, that characterize a natural environment, or the dynamic obstacles and safety issues, that characterize an urban scenario, make the development of an autonomous vehicle a challenging problem. Among the huge number of functionalities that are required to develop an autonomous vehicle, path planning, and trajectory tracking are particularly relevant. On one side the planner has the responsibility to compute a trajectory that takes the vehicle to a desired location, being also feasible, i.e., compatible with the vehicle kino-dynamic constraints, and safe. On the other side the behavior of the vehicle is directly related to the trajectory tracking controller and to the interaction between this system and the localization module.