Swarm Of Mobile Robots Research Articles

Adaptive Flocking of Robot Swarms: Algorithms and Properties

This paper presents a distributed approach for adaptive flocking of swarms of mobile robots that enables to navigate autonomously in complex environments populated with obstacles. Based on the observation of the swimming behavior of a school of fish, we propose an integrated algorithm that allows a swarm of robots to navigate in a coordinated manner, split into multiple swarms, or merge with other swarms according to the environment conditions. We prove the convergence of the proposed algorithm using Lyapunov stability theory. We also verify the effectiveness of the algorithm through extensive simulations, where a swarm of robots repeats the process of splitting and merging while passing around multiple stationary and moving obstacles. The simulation results show that the proposed algorithm is scalable, and robust to variations in the sensing capability of individual robots.

Self-organized flocking in mobile robot swarms

In this paper, we study self-organized flocking in a swarm of mobile robots. We present Kobot, a mobile robot platform developed specifically for swarm robotic studies. We describe its infrared-based short range sensing system, capable of measuring the distance from obstacles and detecting kin robots, and a novel sensing system called the virtual heading system (VHS) which uses a digital compass and a wireless communication module for sensing the relative headings of neighboring robots.

Distributed algorithms for partitioning a swarm of autonomous mobile robots

A number of recent studies address systems of mobile autonomous robots from a distributed computing point of view. Although such systems employ robots that are relatively weak and simple (i.e., dimensionless, oblivious and anonymous), they are nevertheless expected to have strong fault tolerance capabilities as a group. This paper studies the partitioning problem, where n robots must divide themselves into k size-balanced groups, and examines the impact of common orientation on the solvability of this problem. First, deterministic crash-fault-tolerant algorithms are given for the problem in the asynchronous full-compass and semi-synchronous half-compass models, and a randomized algorithm is given for the semi-synchronous no-compass model. Next, the role of common orientation shared by the robots is examined. Necessary and sufficient conditions for the partitioning problem to be solvable are given in the different timing models. Finally, the problem is proved to be unsolvable in the no-compass synchronous model.

A geometric approach to deploying robot swarms

We discuss the fundamental problems and practical issues underlying the deployment of a swarm of autonomous mobile robots that can potentially be used to build mobile robotic sensor networks. For the purpose, a geometric approach is proposed that allows robots to configure themselves into a two-dimensional plane with uniform spatial density. Particular emphasis is paid to the hole repair capability for dynamic network reconfiguration. Specifically, each robot interacts selectively with two neighboring robots so that three robots can converge onto each vertex of the equilateral triangle configuration. Based on the local interaction, the self-configuration algorithm is presented to enable a swarm of robots to form a communication network arranged in equilateral triangular lattices by shuffling the neighbors. Convergence of the algorithms is mathematically proved using Lyapunov theory. Moreover, it is verified that the self-reparation algorithm enables robot swarms to reconfigure themselves when holes exist in the network or new robots are added to the network. Through extensive simulations, we validate the feasibility of applying the proposed algorithms to self-configuring a network of mobile robotic sensors. We describe in detail the features of the algorithm, including self-organization, self-stabilization, and robustness, with the results of the simulation.

Final word: Swarming nurses

It may not be long before swarms of tiny mobile robots will be giving a hand to nurses and medical orderlies in hospitals.

自律移動ロボットの群移動制御のための座標系平均化手法

Previously, the authors have proposed a scheme for collective control of a swarm of autonomous mobile robots. It enables a human operator to effectively control the geometrical center of the swarm only via bird-view observation and a broadcast command. However, for such control, it seems necessary that the operator and the every agent of the swarm refers to the same coordinate system. In this paper, first, the influences of deviations of coordinates among the operator and the agents due to dead-reckoning are examined theoretically. The result shows that, though the deviation between the operator and the average of the agents can easily be compensated by the operator, those among the agents lead to poor maneuverability and performance of the collective manual control. Thus, a method called COMPASS-CC is introduced which can merge the coordinate systems close enough among all the agents in a fully distributed way and without any global localization scheme, by extending the previously proposed method COMPASS. Besides, its effectiveness is analyzed both theoretically and by simulation. The equation for the practical estimation of the steady-state performance is derived and verified. Finally, the validity of the method is confirmed through manual control experiments using a swarm control simulator.

Teamwork by swarms of all terrain mobile robots

The classic monolithic design of robot agents shows all its limits when tasks require capabilities which go beyond those initially planned. Robot collaboration seems to be a possible answer to the otherwise ever increasing complexity of mechanical and electrical design. Swarm robotics, by exploiting the power of interaction among members, offers such an answer. Simple units can in fact collaborate in achieving their common goal without the need of being aware at all of the rest of the group. The resilience achieved in this way makes the paradigm very appealing in all those applications, where mechanical or software failure may jeopardise the success of the overall mission. The present work summarizes the ongoing research which is being carried out by the author and his team. The hardware and software employed as well as some application experiments are described and discussed.

Adaptive Shape Reconfiguration of a Decentralized Motile System Exploiting Molecular Dynamics and Stokesian Dynamics Methods

This paper discusses a fully decentralized algorithm able to create a coherent swarm of autonomous mobile robots from the viewpoint of computational physics. To this end, we focus on Molecular Dynamics and Stokesian Dynamics, both of which are widely used to investigate many-body systems. To verify the feasibility of our approach, this idea has been implemented to a swarm of 2-D radio-connected autonomous mobile robots as a practical example. Simulation results indicate that the proposed algorithm can control the shape of the swarm appropriately based on the current situation without losing the coherence of the swarm nor exchanging global information among modules. Furthermore, we found that local interaction used to exploit Stokesian Dynamics plays an essential role to maintain the coherence of the swarm particularly in an unstructured environment.

Motion Control of Family Mobile Robots with Hierarchical Cooperative Behavior

This paper presents a control architecture of swarms of mobile robots within a framework of hierarchical cooperative control system. A parent-children and a leader-followers types robot system that moves in unstructured environments is proposed. The simulation results confirmed that this hierarchical structure is effective for finding and transporting the objectives, and for obstacles avoidance.