Modified Artificial Potential Field Method for Online Path Planning Applications

Farid Bounini (1) , Denis Gingras (1) , Hervé Pollart (2) , Dominique Gruyer (3)

1 UdeS - Université de Sherbrooke
2 Opal-RT - OPAL-RT Technologies
3 IFSTTAR/COSYS/LIVIC - Laboratoire sur les Interactions Véhicules-Infrastructure-Conducteurs

This paper presents a modified potential field method for robot navigation. The approach overcomes the wellknown artificial potential field (APF) method issue, which is due to local minima that induce the standard APF method to trap in. Thus, the standard APF method is no longer useful in such case. The advantage of the new proposed method, as opposed to those that resort to the global optimization methods, is the low computing time that lines up with the standard A-Star (A*) method. The strategy consists of looking for a practical path in the potential field-according to the potential gradient descent algorithm (PGDA)-and adding a repulsive potential to the current state, in case of blocking configuration, a local minimum. When the PGDA reaches the global minimum, a new potential field will be constructed with only one minimum that matches the final destination of the robot, the global minimum. Finally, to determine the achievable trajectory, a second iteration is performed by the PGDA.

Mots clés: PATH PLANNING; ARTIFICIAL POTENTIAL FIELD METHOD; POTENTIAL GRADIENT DESCENT ALGORITHM; ALGORITHM

Mots clés: INTELLIGENCE ARTIFICIELLE; POTENTIEL ELECTRIQUE; METHODE; ALGORITHME

Domaines: Automatique / Robotique

Farid Bounini, Denis Gingras, Hervé Pollart, Dominique Gruyer. Modified Artificial Potential Field Method for Online Path Planning Applications. IEEE Intelligent Vehicle symposium 2017, Jun 2017, Redondo Beach, United States. pp.180-185, ⟨10.1109/IVS.2017.7995717⟩. ⟨hal-01671469⟩