This paper proposes a decentralized approach for solving the problem of moving a swarm of agents into a desired formation. We propose a decentralized assignment algorithm which prescribes goals to each agent using only local information. The assignment results are then used to generate energy-optimal trajectories for each agent which have guaranteed collision avoidance through safety constraints. We present the conditions for optimality and discuss the robustness of the solution. The efficacy of the proposed approach is validated through a numerical case study to characterize the framework's performance on a set of dynamic goals.
Several approaches to building cohesive formations in robotic systems have been proposed, such as formations built from triangular sub-structures @cite_21 @cite_23 , where a scalable formation is achieved through constructing a series of isosceles triangles. Methods inspired by crystal growth @cite_18 and lattices structures @cite_27 .
@cite_27 @cite_18 @cite_21 @cite_23
2127113638 2562209965 1529395605
We address the problem of deploying a swarm of autonomous mobile robots toward building an ad hoc network of robotic sensors with spatial uniform density. For the purpose, each of the robots configures themselves into an area with geographical constraints through local interactions with two adjacent neighboring robots. The basic idea underlying this work is that robots can be thought of as liquid particles that change their positions conforming to the shape of the container they occupy. The main challenge is how to cope with the accuracy limitations of sensors and possible holes in the configuration. Considering such realistic conditions, the convergence of the proposed method is proved using Lyapunovpsilas theorem. The proposed method is verified to be effective through the simulation for the secure deployments of robotic sensor network. We describe a new decentralized algorithm for multi-robot systems to form arbitrary repeated lattice patterns. Prior work showed how to represent a desired pattern using a directed graph in which each edge is labeled with a rigid body transformation, and proposed an algorithm that accepts this graph as input and computes destinations for each robot using only local information. In this paper, we improve upon that result by describing a new algorithm, substantially different both in message passing procedure and in movement strategy, to resolve several limitations of the existing algorithm. We prove that, by executing this algorithm, the robots will form the desired lattice pattern in a bounded amount of time. We further show that, if the robots' communication graph is connected at the start of the algorithm, it will remain connected throughout the algorithm's execution. Using a simulation, we demonstrate that this algorithm works correctly for systems with dozens of autonomous robots to form various lattice patterns. Moreover, the experiments show a significant improvement in solution quality for our new algorithm compared to the previous approach. The study investigates the leader-follower formation control problem, for which the objective is to control a group of robots such that they move as a rigid formation with a prescribed constant velocity. It is assumed in the study that there are two leader robots, who are the only robots in the group that are informed about the prescribed velocity. All the other robots are followers and do not have the reference velocity information. The authors take the robotic formation as coupled triangular sub-formations and develop adaptive control strategies to enable each follower robot to attain and maintain a stable triangular formation with respect to its two leading neighbours. As a result, the whole group forms a rigid formation. Analyses on convergence and stability properties of equilibrium formations are provided, which show that the desired formation is asymptotically stable. Finally, simulations are given to illustrate our results.