Teamwork in a swarm of robots: an experiment in search and retrieval

In this thesis, we investigate the problem of path formation and prey retrieval in a swarm of robots. We present two swarm intelligence control mechanisms used for distributed robot path formation. In the first, the robots form linear chains. We study three variants of robot chains, which vary in the degree of motion allowedto the chain structure. The second mechanism is called vectorfield. In this case,the robots form a pattern that globally indicates the direction towards a goal orhome location. Both algorithms were designed following the swarm robotics controlprinciples: simplicity of control, locality of sensing and communication, homogeneityand distributedness.We test each controller on a task that consists in forming a path between twoobjects—the prey and the nest—and to retrieve the prey to the nest. The difficultyof the task is given by four constraints. First, the prey requires concurrent, physicalhandling by multiple robots to be moved. Second, each robot’s perceptual rangeis small when compared to the distance between the nest and the prey; moreover,perception is unreliable. Third, no robot has any explicit knowledge about theenvironment beyond its perceptual range. Fourth, communication among robots isunreliable and limited to a small set of simple signals that are locally broadcast.In simulation experiments we test our controllers under a wide range of conditions,changing the distance between nest and prey, varying the number of robotsused, and introducing different obstacle configurations in the environment. Furthermore,we tested the controllers for robustness by adding noise to the different sensors,and for fault tolerance by completely removing a sensor or actuator. We validate thechain controller in experiments with up to twelve physical robots. We believe thatthese experiments are among the most sophisticated examples of self-organisationin robotics to date.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished