In this letter, inspired by the needs of the European H2020 Project PANTHEON,11[Online]. Available: https://www.project-pantheon.eu. we propose a full navigation stack purposely designed for the autonomous navigation of Ackermann steering vehicles in precision farming settings. The proposed stack is composed of a local planner and a pose regulation controller, both implemented in ROS. The local planner generates, in real-Time, optimal trajectories described by a sequence of successive poses. The planning problem is formulated as a real-Time cost-function minimization problem over a finite time horizon where the Ackermann kinematics and the presence of obstacles are encoded as constraints. The control law ensures the convergence toward each of these poses. To do so, in this letter we propose a novel non-smooth control law designed to ensure the solvability of the pose regulation problem for the Ackermann vehicle. Theoretical characterization of the convergence property of the proposed pose regulation controller is provided. Numerical simulations along with real-world experiments are provided to corroborate the effectiveness of the proposed navigation strategy.

Carpio, R.F., Potena, C., Maiolini, J., Ulivi, G., Rossello, N.B., Garone, E., et al. (2020). A Navigation architecture for ackermann vehicles in precision farming. IEEE ROBOTICS AND AUTOMATION LETTERS, 5(2), 1103-1110 [10.1109/LRA.2020.2967306].

A Navigation architecture for ackermann vehicles in precision farming

Carpio R. F.;Potena C.;Maiolini J.;Ulivi G.;Gasparri A.
2020

Abstract

In this letter, inspired by the needs of the European H2020 Project PANTHEON,11[Online]. Available: https://www.project-pantheon.eu. we propose a full navigation stack purposely designed for the autonomous navigation of Ackermann steering vehicles in precision farming settings. The proposed stack is composed of a local planner and a pose regulation controller, both implemented in ROS. The local planner generates, in real-Time, optimal trajectories described by a sequence of successive poses. The planning problem is formulated as a real-Time cost-function minimization problem over a finite time horizon where the Ackermann kinematics and the presence of obstacles are encoded as constraints. The control law ensures the convergence toward each of these poses. To do so, in this letter we propose a novel non-smooth control law designed to ensure the solvability of the pose regulation problem for the Ackermann vehicle. Theoretical characterization of the convergence property of the proposed pose regulation controller is provided. Numerical simulations along with real-world experiments are provided to corroborate the effectiveness of the proposed navigation strategy.
Carpio, R.F., Potena, C., Maiolini, J., Ulivi, G., Rossello, N.B., Garone, E., et al. (2020). A Navigation architecture for ackermann vehicles in precision farming. IEEE ROBOTICS AND AUTOMATION LETTERS, 5(2), 1103-1110 [10.1109/LRA.2020.2967306].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/377128
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