Group Of Mobile Autonomous Agents Research Articles

Coverage control of mobile agents using multi-step broadcast control

AbstractThis paper proposes a novel multi-step broadcast control (MBC) scheme to deploy a group of autonomous mobile agents for accomplishing coverage tasks in a bounded region. Traditional broadcast control (BC) schemes use a one-to-all communication framework to transmit a uniform signal to all agents, making it cost-effective compared with any all-to-all communication-based scheme for a multi-agent system. However, as BC schemes are based on a single-step view of the environment for decision-making, the environment’s varying distribution density is not known immediately to the agents, resulting in suboptimal performance. To overcome this drawback, this paper proposes an MBC scheme, where agents use a predictive multi-step view and are able to detect the varying densities in the environment ahead of time. The local controller output is estimated using a weighted averaging technique which assigns a higher weight to immediate steps; this feature compensates for any decrease in prediction accuracy as the number of steps increases. We demonstrate the effectiveness of the proposed MBC scheme using a coverage task over a region with uneven population density. Compared to existing BC schemes, the proposed MBC scheme shows superior convergence characteristics in task accomplishment and deployment efficiency.

A Cooperative Multiagent Probabilistic Framework for Search and Track Missions

In this work a robust and scalable cooperative multi-agent searching and tracking framework is proposed. Specifically, we study the problem of cooperative searching and tracking of multiple moving targets by a group of autonomous mobile agents with limited sensing capabilities. We assume that the actual number of targets present is not known a priori and that target births/deaths can occur anywhere inside the surveillance region thus efficient search strategies are required to detect and track as many targets as possible. To address the aforementioned challenges we recursively compute and propagate in time the searching-and-tracking (SAT) density. Using the SAT-density, we then develop decentralized cooperative look-ahead strategies for efficient searching and tracking of an unknown number of targets inside a bounded surveillance area.

Distributed Optimal Deployment on a Circle for Cooperative Encirclement of Autonomous Mobile Multi-Agents

A distributed encirclement points deployment scheme for a group of autonomous mobile agents is addressed in this paper. Herein, each agent can measure its own azimuth related to the common target and can at least communicate with its two adjacent neighbors. Given its space-cooperative character, the encirclement points deployment problem is formulated as the coverage control problem on a circle. The measurement range of azimuth sensor is taken into consideration when doing problem formulation, which is closer to the facts in real-world applications. Then, the fully distributed control protocols are put forward based on geometric principle and the convergence is proved strictly with algebraic method. The proposed control protocols can steer the mobile agents to distribute evenly on the circle such that the coverage cost function is minimized, and meanwhile the mobile agents' spatial order on the circle is preserved throughout the systems' evolution. A noteworthy feature of the proposed control protocols is that only the azimuths of a mobile agent and its two adjacent neighbors are needed to calculate the mobile agent's control input, so that the control protocols can be easily implemented in general. Moreover, an adjustable feedback gain is introduced, and it can be employed to improve the convergence rate effectively. Finally, numerical simulations are carried out to verify the effectiveness of the proposed distributed control protocols.

Cooperative Periodic Coverage With Collision Avoidance

In this paper, we propose a periodic solution to the problem of persistently covering a finite set of interest points with a group of autonomous mobile agents. These agents visit periodically the points and spend some time carrying out the coverage task, which we call coverage time. Since this periodic persistent coverage problem is NP-hard, we split it into three subproblems to counteract its complexity. In the first place, we plan individual closed paths for the agents to cover all the points. Second, we formulate a quadratically constrained linear program to find the optimal coverage times and actions that satisfy the coverage objective. Finally, we join together the individual plans of the agents in a periodic team plan by obtaining a schedule that guarantees collision avoidance. To this end, we solve a mixed-integer linear program that minimizes the time in which two or more agents move at the same time. Eventually, we apply the proposed solution to an induction hob with mobile inductors for a domestic heating application and show its performance with experiments on a real prototype.

Geometric Pattern Formation with Coordinated Double-Integrator Agents

Abstract This paper deals with the problem of geometric pattern formation by a group of mobile autonomous agents. The patterns are formed by the trajectories of the agents modeled with double integrator dynamics. The patterns can either be closed or can cover the entire space. We build upon an existing consensus law, by introducing self position feedback and study the collective motion of a team of agents. The patterns are not only aesthetically appealing but can also be used in civilian applications like search, exploration and surveillance. There is no restriction on the underlying graph topology. The control law manipulates the location of the eigenvalues of the overall system to achieve the pattern. We present simulation results to validate the developed theory.

Distance-based acyclic minimally persistent formations with non-steepest descent control

In this paper, we propose a control law to maneuver a group of mobile autonomous agents in the plane, where the information architecture among the agents is modeled by a directed graph. The objective is to achieve a prescribed formation shape by adjusting the inter-agent distances only, which is called the distance-based formation control. The proposed control law uses only relative position measurements so that each agent achieves its control objective in a decentralized manner. On the basis of the proposed control law, we analyze the convergence property of squared-distance errors. We first study a triangular formation and then extend the results of to acyclic minimally persistent formations having more than three agents. We also examine the formation including a moving leader. Numerical simulations and experiments with mobile robot platform are included.

Containment control of multi-agent systems with fixed time-delays in fixed directed networks

Containment control of multi-agent system with time-delays is a meaningful topic with considerable realistic significance in the research of multi-agent systems. This paper investigates the distributed containment control of a group of mobile autonomous agents with multiple stationary or dynamic leaders, when considering the fixed time-delay under fixed directed network topologies. In the case of studying the multi-agent delayed system with continuous-time, Laplace transform and final value theorem are employed. Specifically some sufficient conditions are obtained which can ensure the containment of the first-order multi-agent systems. Moreover, an effective control protocol is designed for the first-order discrete-time systems with fixed time-delays. Finally, simulation examples are given to verify the effectiveness of the theoretical results and conclusions.

Nonuniform Deployment of Autonomous Agents in Harbor-Like Environments

We propose a nonuniform deployment strategy of a group of homogeneous autonomous agents in harbor-like environments. High value units berthed in the area need to be secured against external attacks. Defenders deployed in the area are expected to monitor, intercept, engage, and neutralize threats. In the framework of decentralized coordinated multi-agent systems, we model and simulate the optimal deployment of a group of mobile autonomous agents that accounts for a risk map of the area and the optimal trajectories that minimize the energy consumed to intercept a threat in a given area of interest. Theoretical results are numerically illustrated through simulations in a realistic harbor protection scenario.

Distributed formation control of mobile autonomous agents using relative position measurements

In this study, we consider an acyclic rigid formation with a group of mobile autonomous agents moving in a two-dimensional space. The formation is generated via a Henneberg sequence construction in which there is one global leader that does not follow any other agents, one first-follower that only follows the global leader, and each of other agents has two leaders, which is added by a vertex addition or an edge splitting operation. The entire formation moves with the leadership of the global leader. Every follower agent tries to maintain distances towards its leaders. Under the constraint of the acceleration for the global leader, the distributed formation control laws are proposed for the followers that only use the locally relative distance measurement. The control law of the first-follower is proposed, which needs to know the velocity of the global leader and the relative distance between the global leader and itself. The global asymptotic stability of the expected formation is proved via a Lyapunov-based technique for the considered multi-agent system. Moreover, the stable rigidity problem of a formation is investigated for the proposed distributed relative position-only formation control law. Necessary and sufficient conditions are provided that must be satisfied by the architecture of the underlying graph. Simulation results illustrate the effectiveness of the proposed formation control approach.

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)

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 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.

Consensus control for multi-agent systems with double-integrator dynamics and time delays

In this study, mathematical modelling and analysis for consensus problems will be conducted for a group of autonomous mobile agents with double-integrator dynamics and time-varying interconnection delays. To solve the problems, distributed control scheme for each agent will be proposed first. Then the consensus stability of the multi-agent system is obtained for the problem, where the dynamics of each agent is second-order with time-varying interconnection delays. In the convergence analysis, both fixed and switched interconnection topologies of the considered multi-agent system are investigated. Finally, some numerical examples are presented to validate the consensus algorithms.

Collective motion in non-reciprocal swarms

This paper studies a non-reciprocal swarm model that consists of a group of mobile autonomous agents with an attraction-repulsion function governing the interaction of the agents. The function is chosen to have infinitely large values of repulsion for vanishing distance between two agents so as to avoid occurrence of collision. It is shown analytically that under the detailed balance condition in coupling weights, all the agents will aggregate and eventually form a cohesive cluster of finite size around the weighted center of the swarm in a finite time. Moreover, the swarm system is completely stable, namely, the motion of all agents converge to the set of equilibrium points. For the general case of non-reciprocal swarms without the detailed balance condition, numerical simulations show that more complex self-organized oscillations can emerge in the swarms. The effect of noise on collective dynamics of the swarm is also examined with a white Gaussian noise model.

Robust Consensus and Soft Control of Multi-Agent Systems with Noises*

This paper considers the problem of robust consensus for a basic class of multi-agent systems with bounded disturbances and with directed information flow. A necessary and sufficient condition on the robust consensus is first presented, which is then applied to the analysis, control and decision making problems in the noise environments. In particular, the authors show how a soft control technique will synchronize a group of autonomous mobile agents without changing the existing local rule of interactions, and without assuming any kind of connectivity conditions on the system trajectories.

Flocking in multi‐agent systems with multiple virtual leaders

AbstractMany tracking problems in flocking are related to a single (virtual) leader with a constant velocity. In this paper, we investigate the problem of controlling a group of mobile autonomous agents to track multiple virtual leaders with varying velocities in the sense that agents with the same virtual leader attain the same velocity and track the corresponding leader. We propose a provably‐stable flocking algorithm. Moreover, we show that the position and velocity of the center of the mass of all agents will exponentially converge to weighted average position and velocity of the virtual leaders. Numerical simulations are worked out to illustrate theoretical results. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Reaching a Consensus in a Dynamically Changing Environment: Convergence Rates, Measurement Delays, and Asynchronous Events

This paper uses recently established properties of compositions of directed graphs together with results from the theory of nonhomogeneous Markov chains to derive worst case convergence rates for the headings of a group of mobile autonomous agents which arise in connection with the widely studied Vicsek consensus problem. The paper also uses graph-theoretic constructions to solve modified versions of the Vicsek problem in which there are measurement delays, asynchronous events, or a group leader. In all three cases the conditions under which consensus is achieved prove to be almost the same as the conditions under which consensus is achieved in the synchronous, delay-free, leaderless case.

Generalization of nonlinear cyclic pursuit

In this paper, some generalizations of the problem of formation of a group of autonomous mobile agents under nonlinear cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i + 1 modulo n. Each agent is subjected to a nonholonomic constraint. A necessary condition for equilibrium formation to occur among a group of agents with different speeds and different controller gains is obtained. These results generalize equal speed and equal controller gain results available in the literature.