Decentralized Multi-Phase Formation Control for Cattle Herding

Herding is performed by people or trained ani- mals to control the movement of livestock under the desired direction of an operator. This paper presents a novel decentral- ized control strategy for a group of robots to herd animals which consists of two phases, a surrounding phase and a driving phase. In the surrounding phase, a custom artificial potential field is employed to simultaneously guide the robots to encircle the herd by tracking the outmost animals and maintaining a safe distance from other neighboring robots. Once the encirclement is complete, the robots transition to drive the animals toward a designated goal by simply maintaining their initial formation and traversing to it. Unlike existing works on herding using flocking control, local observations of the nearest animals and communication with other robots within the sensing range are the only requirements for the robots to surround and herd the animals effectively. Moreover, the animal-robot behavior model resembles the interaction of livestock in the presence of an external predatory threat, where robots act as predators. An analytical proof and empirical results collected from different simulators demonstrate that the proposed control enables the robots to converge around the boundary of the animals and guide them toward the designated goal.