In this work we consider a swarm of agents shaped as bars with a certain orientation in the state space. Members of the swarm have to reach an aggregate state, while guaranteeing the collision avoidance and possibly achieving an angular consensus. By relying on a segment-to-segment distance definition, we propose a control law, which guides the agents towards this goal. A theoretical analysis of the proposed control scheme along with simulations and experimental results is provided. The proposed framework can be used to model several application scenarios ranging from collaborative transportation to precision farming, where each agent may represent either a large robot or a group of robots intent to carry bar-like shaped loads. Representative examples include: a fleet of robot-teams performing a collaborative object transportation task in an automated logistic setting, or a fleet of autonomous tractors each carrying a large atomizer to spray chemical products for pest and disease control in a precision farming setting.
Carpio, R.F., Di Giulio, L., Garone, E., Ulivi, G., Gasparri, A. (2018). A Distributed Swarm Aggregation Algorithm for Bar Shaped Multi-Agent Systems. In IEEE International Conference on Intelligent Robots and Systems (pp.4303-4308). Institute of Electrical and Electronics Engineers Inc. [10.1109/IROS.2018.8594236].
A Distributed Swarm Aggregation Algorithm for Bar Shaped Multi-Agent Systems
CARPIO, RENZO FABRIZIO;Ulivi G.;Gasparri A.
2018-01-01
Abstract
In this work we consider a swarm of agents shaped as bars with a certain orientation in the state space. Members of the swarm have to reach an aggregate state, while guaranteeing the collision avoidance and possibly achieving an angular consensus. By relying on a segment-to-segment distance definition, we propose a control law, which guides the agents towards this goal. A theoretical analysis of the proposed control scheme along with simulations and experimental results is provided. The proposed framework can be used to model several application scenarios ranging from collaborative transportation to precision farming, where each agent may represent either a large robot or a group of robots intent to carry bar-like shaped loads. Representative examples include: a fleet of robot-teams performing a collaborative object transportation task in an automated logistic setting, or a fleet of autonomous tractors each carrying a large atomizer to spray chemical products for pest and disease control in a precision farming setting.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
