Group Of Mobile Agents Research Articles

Robot Coordination Based on Biologically Inspired Methods

An embedded particle swarm optimization (PSO) technique combined with virtual pheromones deposition and rules for artificial bird flocking is proposed to handle an area coverage problem using a swarm of mobile robots. A simulation tool VERA that was developed to simulate a swarm behavior of a group of mobile agents is described. Results of simulation experiments and tests on Lego robots that prove the concept are presented. Results are discussed and future development is suggested in the end of the paper.

Antecedence Graph Approach to Checkpointing for Fault Tolerance in Mobile Agent Systems

The flexibility offered by mobile agents is quite noticeable in distributed computing environments. However, the greater flexibility of the mobile agent paradigm compared to the client/server computing paradigm comes at an additional threats since agent systems are prone to failures originating from bad communication, security attacks, agent server crashes, system resources unavailability, network congestion, or even deadlock situations. In such events, mobile agents either get lost or damaged (partially or totally) during execution. In this paper, we propose parallel checkpointing approach based on the use of antecedence graphs for providing fault tolerance in mobile agent systems. During normal computation message transmission, the dependency information among mobile agents is recorded in the form of antecedence graphs by participating mobile agents of mobile agent group. When a checkpointing procedure begins, the initiator concurrently informs relevant mobile agents, which minimizes the identifying time. The proposed scheme utilizes the checkpointed information for fault tolerance which is stored in form of antecedence graphs. In case of failures, using checkpointed information, the antecedence graphs and message logs are regenerated for recovery and then normal operation continued. Moreover, compared with the existing schemes, our algorithm involves the minimum number of mobile agents during the identifying and checkpoiting procedure, which leads to the improvement of the system performance. In addition, the proposed algorithm is a domino-free checkpointing algorithm, which is especially desirable for mobile agent systems. Quantitative analysis and experimental simulation show that our algorithm outperforms other coordinated checkpointing schemes in terms of the identifying time and the number of blocked mobile agents and then can provide a better system performance. The main contribution of the proposed checkpointing scheme is the enhancement of graph-based approach in terms of considerable improvement by reducing message overhead, execution, and recovery times.

Ant-inspired Decentralized Task Allocation Strategy in Groups of Mobile Agents

This paper presents a hybrid task allocation strategy for decentralized groups of mobile agents. The work is strongly inspired by the biological behavior of social insects. Agent based modeling approach has been used to model the behavior of agents. Environment of the model comprises of set of tasks and heterogeneous groups of mobile agents. Each group of agents follows respective local rules to communicate with neighboring agents and with the environment in their vicinity. The agents can not only carry out their own tasks but can also switch tasks to meet colonial demands. This paper presents an extension of a series of models presented earlier. In earlier models, agents reacted only to stimulus. Although evidence exists of task preferences among castes (bias) in many ant species, little work has been done in investigating the benefits for the colony of such preferences. This paper addresses the role of bias in the colony performance under different environmental circumstances. Experiment results indicate that the model presented in this paper is highly efficient, accurate and consistent with biological equivalents. The model with bias within a group is novel and has not been done before to the best of my knowledge.

A Game Theoretic Approach to Distributed Coverage of Graphs by Heterogeneous Mobile Agents

In this paper, we study the problem of covering an apriori unknown network structure by a group of mobile agents with possibly nonidentical coverage and communication capabilities. The network is represented as a graph, and the agents are mobile devices that explore and cover the graph in a decentralized fashion. We study this problem in a game theoretic setting and achieve optimal coverage through learning in games.

Mobile agent group communication ensuring reliability and totally-ordered delivery

In this paper, an atomic mobile agent group communication protocol is designed to have the following beneficial features. The protocol enables each agent to adaptively choose a small number of forwarders among its visiting nodes based on its decision. Also, it replicates paths on which messages should be transmitted to their targeting mobile agents in an effective manner. The mobile agent group location cache each sending agent keeps in our protocol can considerably speed up message delivery to a group of agents and lower message forwarding load imposing on forwarders. Furthermore, it allows messages destined to a group of agents to be reliably delivered to all surviving agents in the same order despite their mobility and F forwarders’ failures unlike the other existing ones. Simulation results indicate that our protocol considerably performs better than the existing one in terms of message delivery time and location information management overhead.

2A1-O01 自律移動体群による分散輸送の解析(自律分散型ロボットシステム)

2A1-O01 自律移動体群による分散輸送の解析(自律分散型ロボットシステム)

Trust and context view-based knowledge sharing in MANets

Mobile ad-hoc networks (MANets) are self-organised, infrastructure-less networks formed by interaction among the users present in the environment. Due to dynamic nature of MANets, it is difficult for the users to find out peers who are both trustworthy and capable of providing relevant information. To deal with these issues, this paper proposes a trust and context view-based knowledge sharing system (TACKSS) built over a framework of mobile agent groups to coordinate the activities of a group of users. The users are clustered into physical groups (on the basis of their location) and contextual views (on the basis of their academic interest). Cooperation in the system is ensured by awarding trust and reputation-based incentives to the users who participate in knowledge exchange as well as routing processes. The proposed work is validated through a university case study simulated in JADE 4.0 and Netbeans. The results indicate that there is a positive correlation between incentives and cooperative behaviour of the users.

Multiagent Navigation Functions Revisited

This paper presents a methodology to design a control law that can provably steer a group of mobile agents to a free-floating formation of specific shape, while avoiding collisions. We indicate why existing multiagent solutions have a theoretical limitation due to one of the working assumptions of the single-agent potential function approach being violated. A new nonsmooth type of multiagent potential functions is, thus, developed. It is shown how this extension of the navigation function concept to multiagent systems ensures the nondegeneracy of the critical points of the potential function.

Multiple Criteria Clustering of Mobile Agents in WSN

In Wireless sensor networks data aggregation with hundreds and thousands of sensor nodes is very complex task. Recently, mobile agents have been proposed for efficient data dissemination in sensor networks. In the traditional client/server based computing architecture, data is collected from multiple sources and forwarded to destination for further processing. It requires high bandwidth, whereas in the mobile agent is a task specific executable code traverses to the relevant source for gathering data. It reduces communication overhead, reduce cost, low bandwidth. Agents have capability to perform task for multiple applications. It will send only useful information to destination node. The problem is to group similar mobile agents into a number of clusters such that each cluster has similarity in responding to a group of nodes. By clustering intelligent mobile agents, it is possible to reduce the cost of time for each individual agent, decrease the demand imposed on network for a set of required tasks, decrease total number of visits. This paper, we present the problem of Multiple Criteria Clustering of Mobile Agents (MCCMA) where the decision is to cluster mobile agents such that a group of similar intelligent mobile agents will visit a group of similar sensor nodes.

The Modeling and Implementation of Reliable Mobile Agent Systems using Group Communication Services

A mobile agent is a computer program that runs autonomously on behalf of a user and travels through a certain itinerary in a network of computers. When compared with normal client/server architecture, mobile agent paradigm adds up additional reliability problems since agents programs could be totally or partially lost due to failures that come from bad communication or computer agent's crash with the recent increase of considering mobile agent in different E-World applications, reliability is considered as a crucial issue to be faced. Most of existing mobile agent systems considers check pointing or replication as a mechanism in achieving reliable and fault tolerant execution. In this paper we present new model which employs the benefits gained from combing both mechanisms to achieve reliable mobile agent execution. Our model uses group communication services to avail different essential issues such as agent’s synchronization to facilitate the implementation the protocol. The proposed approach is dynamic in the sense that it allows a flexible membership mechanism to join or leave a mobile agent groups used in achieving the reliable execution.

Distributed containment control with multiple stationary or dynamic leaders in fixed and switching directed networks

In this paper, we study the problem of distributed containment control of a group of mobile autonomous agents with multiple stationary or dynamic leaders under both fixed and switching directed network topologies. First, when the leaders are stationary and all followers share an inertial coordinate frame, we present necessary and sufficient conditions on the fixed or switching directed network topology such that all followers will ultimately converge to the stationary convex hull formed by the stationary leaders for arbitrary initial states in a space of any finite dimension. When the directed network topology is fixed, we partition the (nonsymmetric) Laplacian matrix and explore its properties to derive the convergence results. When the directed network topology is switching, the commonly adopted decoupling technique based on the Kronecker product in a high-dimensional space can no longer be applied and we hence present an important coordinate transformation technique to derive the convergence results. The proposed coordinate transformation technique also has potential applications in other high-dimensional distributed control scenarios and might be used to simplify the analysis of a high-dimensional system to that of a one-dimensional system when the decoupling technique based on the Kronecker product cannot be applied. Second, when the leaders are dynamic and all followers share an inertial coordinate frame, we propose a distributed tracking control algorithm without velocity measurements. When the directed network topology is fixed, we derive conditions on the network topology and the control gain to guarantee that all followers will ultimately converge to the dynamic convex hull formed by the dynamic leaders for arbitrary initial states in a space of any finite dimension. When the directed network topology is switching, we derive conditions on the network topology and the control gain such that all followers will ultimately converge to the minimal hyperrectangle that contains the dynamic leaders and each of its hyperplanes is normal to one axis of the inertial coordinate frame in any high-dimensional space. We also show via some counterexamples that it is, in general, impossible to find distribute containment control algorithms without velocity measurements to guarantee that all followers will ultimately converge to the convex hull formed by the dynamic leaders under a switching network topology in a high-dimensional space. Simulation results are presented as a proof of concept.

Distributed observer-based cooperative control of multiple nonholonomic mobile agents

In this article, cooperative output feedback control of a group of nonholonomic mobile agents is considered. Distributed observer-based cooperative control laws are proposed with the aid of Lyapunov techniques and results from graph theory. Robustness of the stability of the closed-loop systems with the proposed control laws is considered. The effectiveness of the proposed controllers is verified by simulation results.

Gossip Coverage Control for Robotic Networks: Dynamical Systems on the Space of Partitions

Future applications in environmental monitoring, delivery of services, and transportation of goods motivate the study of deployment and partitioning tasks for groups of autonomous mobile agents. These tasks may be achieved by recent coverage algorithms, based upon the classic methods by Lloyd. These algorithms, however, rely upon critical requirements on the communication network: information is exchanged synchronously among all agents and long-range communication is sometimes required. This work proposes novel coverage algorithms that require only gossip communication, i.e., asynchronous, pairwise, and possibly unreliable communication. Which robot pair communicates at any given time may be selected deterministically or randomly. A key innovative idea is describing coverage algorithms for robot deployment and environment partitioning as dynamical systems on a space of partitions. In other words, we study the evolution of the regions assigned to each agent rather than the evolution of the agents' positions. The proposed gossip algorithms are shown to converge to centroidal Voronoi partitions under mild technical conditions. Our treatment features a broad variety of results in topology, analysis, and geometry. First, we establish the compactness of a suitable space of partitions with respect to the symmetric difference metric. Second, with respect to this metric, we establish the continuity of various geometric maps, including the Voronoi diagram as a function of its generators, the location of a centroid as a function of a set, and the widely known multicenter function studied in facility location problems. Third, we prove two convergence theorems for dynamical systems on metric spaces described by deterministic and stochastic switches.

Mobile sensor networks for modelling environmental pollutant distribution

This article proposes to deploy a group of mobile sensor agents to cover a polluted region so that they are able to retrieve the pollutant distribution. The deployed mobile sensor agents are capable of making point observation in the natural environment. There are two approaches to modelling the pollutant distribution proposed in this article. One is a model-based approach where the sensor agents sample environmental pollutant, build up an environmental pollutant model and move towards the region where high density pollutant exists. The modelling technique used is a distributed support vector regression and the motion control technique used is a distributed locational optimising algorithm (centroidal Voronoi tessellation). The other is a model-free approach where the sensor agents sample environmental pollutant and directly move towards the region where high density pollutant exists without building up a model. The motion control technique used is a bacteria chemotaxis behaviour. By combining this behaviour with a flocking behaviour, it is possible to form a spatial distribution matched to the underlying pollutant distribution. Both approaches are simulated and tested with a group of real robots.

Distributed Averaging in Dynamic Networks

The question of computing average of numbers present at nodes in a network in a distributed manner using gossip or message-passing algorithms has been of great recent interest across disciplines-algorithms, control and robotics, estimation, social networks, etc. It has served as a non-trivial, representative model for an important class of questions arising in these disciplines and thus guiding intellectual progress over the past few decades. In most of these applications, there is inherent dynamics present, such as changes in the network topology in terms of communication links, changes in the values of numbers present at nodes, and nodes joining or leaving. The effect of dynamics in terms of communication links on the design and analysis of algorithms for averaging is reasonably well understood, e.g., J. Tsitsiklis, “Problems in decentralized decision making and computation,” Ph.D. dissertation, MIT, 1984; D. Bertsekas , “Convergence theories of distributed iterative processes: A survey,” MIT, 1983; A. Jadbabaie , “Coordination of groups of mobile autonomous agents using nearest neighbor rules,” IEEE Trans. on Automatic Control, vol. 48, no. 6, pp. 988-1001, 2003; S. Boyd , “Gossip algorithms: Design, analysis and applications,” Proc. IEEE INFOCOM, 2005, pp. 1653-1664. However, little is known about the effect of other forms of dynamics. In this paper, we study the effect of such types of dynamics in the context of maintaining average in the network. Specifically, we design dynamics-aware message-passing or gossip algorithm that maintains good estimate of average in presence of continuous change in numbers at nodes. Clearly, in presence of such dynamics the best one can hope for is a tradeoff between the accuracy of each node's estimate of the average at each time instant and the rate of dynamics. For our algorithm, we characterize this tradeoff and establish it to be near optimal. The dependence of the accuracy of the algorithm on the rate of dynamics as well as on the underlying graph structure is quantified.

Memoryless cooperative graph search based on the simulated annealing algorithm

We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter—radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment.

On influences of global and local cues on the rate of synchronization of oscillator networks

Synchronization of connected oscillator networks under global and local cues is ubiquitous in both science and engineering. Over the last few decades, enormous attention has been paid to study synchronization conditions of connected oscillators in chemistry, physics, mechanics, and particularly in biology. However, the influences of global and local cues on the rate of synchronization have not been fully studied. It is widespread that synchronization is achieved in the simultaneous presence of both global and local cues, such as intercellular coupling signals and external entrainment signals in terms of biological oscillators, and inter-neighbor coupling signals between follower nodes and central guiding signals in terms of groups of mobile autonomous agents. We prove in this paper that the strength of the global cue is the only determinant of the rate of synchronization. More specifically, we prove that a stronger global cue means a faster rate of synchronization whereas a stronger local cue does not necessarily make the synchronization rate faster. Our results not only apply to the noise-free case, but also apply to the case that the oscillator natural frequencies are subject to white noise. The analysis does not require the interplay to be symmetric or balanced. Simulation results are given to illustrate the proposed results.

Safe Formation Control with Obstacle Avoidance

AbstractIn this paper, we consider the general problem of guaranteeing safe interaction of humans and a group of mobile agents in an environment of interest. The way that we guarantee such a safe interaction is via proposing algorithms that prevent the agents from colliding with environmental obstacles with unknown sizes and locations, e.g. human operators. To do so, we first consider the problem of forcing a set of autonomous agents form a desired formation and follow a trajectory only known to one of them, namely the leader of the formation. Then we build upon the solution given to this problem and solve another problem of interest. This is to guarantee obstacle collision avoidance while the agents are following an unknown trajectory and keeping the desired shape of the formation. The stability of the control laws presented here is analytically established and some simulation results are presented to show the performance of the proposed control laws in different scenarios.

Cooperative and decentralized navigation of autonomous underwater gliders using predictive control

AbstractCoordinated fleet of Autonomous Underwater Gliders (AUGs) can provide significant benefit to a number of marine applications including ocean sampling, mapping, surveillance and communication. Traditional techniques for navigating underwater vehicles have been designed for single-vehicle operations and do not scale well to multi-vehicle operations and missions. In this paper a navigation system for a fleet of AUGs is developed based on Networked Decentralized Model Predictive Control (ND-MPC). The proposed approach coordinates a group of point-mass mobile agents to achieve a desired formation, while avoiding collisions between themselves. In order to obtain collision free paths, the approach integrates the required collision avoidance constraints. The fleet localization is performed by sensor fusion using adaptive extended Kalman filtering. The free collision and convergence properties are verified through simulations results. The proposed approach can be generalized to formation of heterogeneous autonomous agents.

Coordination of Mobile Agents in Flocks with Time-varying Interactions

AbstractIn this paper, we develop a novel self-propelled particle model to describe the emergent behavior of a group of mobile agents. All agents coordinate with their neighbors through local social forces accounting for velocity alignment and collision avoidance. We allow the interaction ranges to adapt to the group density. This range adaption results in topology changes as well as discontinuities in those social forces. We apply differential inclusion technique to analyze the convergence properties of the proposed control method. The analytical and numerical results show that all the agents eventually align their velocities and avoid collisions with each other no matter how fast the topology changes.