Apr 23, 2026 · cs.ROJ/K move · Enter open · S save
Adrian Baruck, Michael Dubé, Christoph Steup, Sanaz Mostaghim
1*Chair of Computational Intelligence, Otto-von-Guericke-University, Universitätsplatz 2, Magdeburg, 39106, Germany. · 2Fraunhofer Institute for Transportation and Infrastructure Systems2026 IVI, Zeunerstr. 38, Dresden, 01069, Germany.
In this paper, we aim to extend the traditional point-mass-like robot representation in swarm robotics and instead study a swarm of long Heavy Articulated Vehicles (HAVs). HAVs are kinematically constrained, elongated, and articulated, introducing unique challenges. Local, decentralized coordination of these vehicles is motivated by many real-world applications. Our approach, Prevent-Jack, introduces the sparsely covered context steering framework in robotics. It fuses six local behaviors, providing guarantees against jackknifing and collisions at the cost of potential dead- and livelocks, tested for vehicles with up to ten trailers. We highlight the importance of the Evade Attraction behavior for deadlock prevention using a parameter study, and use 15,000 simulations to evaluate the swarm performance. Our extensive experiments and the results show that both the dead- and livelocks occur more frequently in larger swarms and denser scenarios, affecting a peak average of 27%/31% of vehicles. We observe that larger swarms exhibit increased waiting, while smaller swarms show increased evasion.