Coordination Of Multi-robot Systems Research Articles

Fuzzy k-Winner-Take-All Network for Competitive Coordination in Multirobot Systems

Fuzzy <i>k</i>-Winner-Take-All Network for Competitive Coordination in Multirobot Systems

Obstacle Avoidance in Distributed Optimal Coordination of Multi-Robot Systems: A Trajectory Planning and Tracking Strategy

Obstacle Avoidance in Distributed Optimal Coordination of Multi-Robot Systems: A Trajectory Planning and Tracking Strategy

Hunting strategy for multi-robot based on wolf swarm algorithm and artificial potential field

The cooperation and coordination in multi-robot systems is a popular topic in the field of robotics and artificial intelligence, thanks to its important role in solving problems that are better solved by several robots compared to a single robot. Cooperative hunting is one of the important problems that exist in many areas such as military and industry, requiring cooperation between robots in order to accomplish the hunting process effectively. This paper proposed a cooperative hunting strategy for a multi-robot system based on wolf swarm algorithm (WSA) and artificial potential field (APF) in order to hunt by several robots a dynamic target whose behavior is unexpected. The formation of the robots within the multi-robot system contains three types of roles: the leader, the follower, and the antagonist. Each role is characterized by a different cognitive behavior. The robots arrive at the hunting point accurately and rapidly while avoiding static and dynamic obstacles through the artificial potential field algorithm to hunt the moving target. Simulation results are given in this paper to demonstrate the validity and the effectiveness of the proposed strategy.

Generalized Coordination of Multi-robot Systems

Generalized Coordination of Multi-robot Systems

Multi-Robot Control Inspired by Bacterial Chemotaxis: Coverage and Rendezvous via Networking of Chemotaxis Controllers

This paper presents networked controllers for the coordination of multi-robot systems, inspired by the chemotaxis of bacteria. Chemotaxis is a biological phenomenon wherein each organism senses the concentration of a chemical in its environment and moves to the highest (or lowest) concentration point. The problem studied herein is a coverage problem, specifically, the problem of finding networked controllers to deploy robots so that they are located uniformly on a given space. To solve this problem, we decompose a global performance index quantifying the achieved degree of coverage into local indices that can be calculated in a distributed manner over the network of robots. By combining this with a controller causing chemotaxis, we present a solution to the coverage problem wherein each robot performs either a forward movement or random rotation based on the local performance index at each time step. Moreover, we extend this solution to rendezvous at an unspecified point. Simulation and experimental results demonstrate that our solution achieves coverage and rendezvous only via the above two types of robot movements and can handle different tasks simply by changing the global performance index, through the appropriate use of the chemotaxis controller.

A Multi-robot System Coordination Design and Analysis on Wall Follower Robot Group

In this research, multi-robot formation can be established according to the environment or workspace. Group of robots will move sequently if there is no space for robots to stand side by side. Leader robot will be on the front of all robots and follow the right wall. On the other hand, robots will move side by side if there is a large space between them. Leader robot will be tracked the wall on its right side and follow on it while every follower moves side by side. The leader robot have to broadcast the information to all robots in the group in radius 9 meters. Nevertheless, every robot should be received information from leader robot to define their movements in the area. The error provided by fuzzy output process which is caused by read data from ultrasound sensor will drive to more time process. More sampling can reduce the error but it will drive more execution time. Furthermore, coordination time will need longer time and delay. Formation will not be establisehed if packet error happened in the communication process because robot will execute wrong command.

Agent-based modelling of multi-robot systems

Multi-robot systems can be used in various industrial and non-industrial applications such as manufacturing, environmental monitoring, disaster rescue missions or agricultural foraging. In this context, different problems need to be solved: robot control, robot perception, multi-robot system coordination, global and local planning/re-planning etc. For example, choosing a good coordination mechanism is a difficult task that depends on the application and can be done via trial and error experiments and comparative studies. Some guidelines can be learned from the case studies reported in the literature. Moreover, artificial intelligence provides several techniques (e.g. rule-based systems, machine learning, artificial neural networks, swarm intelligence) that can improve the performances of multi-robot systems coordination. Regarding experimental comparative studies between different methods, a cheaper solution is given by simulations. On the other hand, knowledge sharing between robots can be provided by ontologies that facilitate the inter-robot communication as a base of multi-robot system coordination. Our research work focus on modelling a multi-robot system as an agent based system which is a proper choice for distributed systems and enables simulations. In this paper we present an agent-based model for multi-robot systems that use a common ontology and reinforcement learning as agent adaptation ability. An application for environmental quality monitoring is discussed.

Type synthesis of coordinated multi-robot system based on parallel thought

For the synthesis of the required type about the multi-robot coordination system in industrial transportation, this paper presents a novel method in which each robot in the coordinated task is viewed as a branched chain of an equivalent parallel robot (EPR), which is converted into a problem for type synthesis of parallel robots. A theoretic method is proposed to represent the kinematic features of the mechanism’s end-effector and its position and pose in the world coordinate system. The basic concept of a robotic characteristic (C) set is given, and the corresponding algorithm is analyzed. Based on the theory of C set, the concrete steps for type synthesis of EPR are presented by analyzing the characteristics of its branched chains, and many EPR groups with end kinematic features for the C sets of the operational tasks are obtained. Then three translational (3T) operational requirements that can be extended to other degrees of freedom (DOF) are adopted, and the DOF of homogeneous and heterogeneous EPR are analyzed using screw theory. Finally the validation of the method is demonstrated by Adams, which shows that the two groups are able to complete the task.

Exploration Strategies of Coordinated Multi-Robot System: A Comparative Study

Environment Exploration is the basic process that most of Multi Robot Systems applications depend on it. The exploration process performance depends on the coordination strategy between the robots participating in the team.  In this paper the coordination of Multi Robot Systems in the exploration process is surveyed, and the performance of different Multi Robot Systems exploration strategies is contrasted and analyzed for different environments and different team sizes.

Integrating predicate reasoning and reactive behaviors for coordination of multi-robot systems

To overcome computational expensive problem in coordination of multi-robot systems (MRS) for unknown environment explorations, an integrated coordinated algorithm is proposed in this paper. The algorithm integrated predicate based reasoning and reactive behaviors to realize coordination and obstacle avoidance. An MRS partitioning strategy is proposed to reduce the scale of problem. Then, an initialization strategy realizes dispersion of robots over the environment, and task assignments at the beginning. When a robot has finished its task, predicate based reasoning is used to assign task and to realize cooperative exploration among robots. Robots explore the unknown environment through a series of zigzag trajectories. To deal with obstacle avoidance, a few of reactive behaviors are defined. Supervisors are resident in middle level of a hierarchical architecture for each robot. The results are validated by computer simulations.

Integrating planned and reactive behaviors for exploration coordination of multi-robot systems

To realize efficient exploration, a novel coordinated algorithm which integrated planned and reactive behaviors is proposed in this paper. The planned behaviors realize dispersion of robots over an environment, cooperation among robots and task assignments to robots. The behaviors are discussed fro m a case that the robot team size equals four in a kind of obstacle free environments. Afterwards, the behaviors are used to coordinate robot team with any size by utilizing a concept of compound robot. Reactive behaviors are used to deal with appearance of different outline obstacles in a kind of sparsely occupied environments. Then, a finite state machine is utilized to integrate these behaviors. For the two kinds of environments, robots conduct a set of zigzag and distorted zigzag trajectories, respectively. Finally, the results are validated by computer simulations.

Advanced approaches for multi-robot coordination in logistic scenarios

Robotics technology has recently matured sufficiently to deploy autonomous robotic systems for daily use in several applications: from disaster response to environmental monitoring and logistics. In such applications, robots must establish collaborative interactions so to achieve their individual and collective goals and a key problem is for robots to make individual decisions so to optimize a system wide objective function. This problem is typically referred to as coordination. In this paper, we first describe modern optimization techniques for coordination in multiRobot systems. Specifically, we focus on approaches that are based on algorithms widely used to solve graphical models and constraint optimization problems, such as the max-sum algorithm. We then analyze the coordination problem faced by a set of robots operating in a warehouse logistic application. In this context robots must transport items from loading to unloading bays so to complete packages to be delivered to customers. Robots must cooperate to maximize the number of packages completed in the unit of time. To this end a crucial component is to avoid interferences when moving in the environment. We show how such problem can be formalized as a Distributed Constrained Optimization problem and we provide a solution based on the binary max-sum algorithm. Finally, we provide a quantitative evaluation of our approach in a simulated scenario using standard robotics tools (ROS and Gazebo).

Cooperative exploration based on supervisory control of multi-robot systems

When multiple mobile robots cooperatively explore an unknown environment, the advantages of robustness and redundancy are guaranteed. However, available traditional economy approaches for coordination of multi-robot systems (MRS) exploration lack efficient target selection strategy under a few of situations and rely on a perfect communication. In order to overcome the shortages and endow each robot autonomy, a novel coordinated algorithm based on supervisory control of discrete event systems and a variation of the market approach is proposed in this paper. Two kinds of utility and the corresponding calculation schemes which take into account of cooperation between robots and covering the environment in a minimal time, are defined. Different moving target of each robot is determined by maximizing the corresponding utility at the lower level of the proposed hierarchical coordinated architecture. Selection of a moving target assignment strategy, dealing with communication failure, and collision avoidance are modeled as behaviors of each robot at the upper level. The proposed approach distinctly speeds up exploration process and reduces the communication requirement. The validity of our algorithm is verified by computer simulations.

Hierarchical Coordination for Multi-Robot Systems with Region-Based Tracking Control

This paper presents a control framework for hierarchical coordination of multi-robot system by using leader-follower and region-based approaches. The leader robot is controlled to converge to and circulate along a closed curve that is defined by an implicit function. In the proposed control framework, only the leader robot has the knowledge of the desired curve, and the follower robots are controlled to track the curve indirectly through the leader robot. In order to enhance redundancy and flexibility of multi-robot systems in practice the follower robots are controlled to stay freely within a designated regions surrounding the leader robot. Moreover, the group of follower robots are able to circulate in the specified region for the sake of enlarging the sensing areas. The stability and convergence of the proposed multi-robot system with the addressed control algorithms are studied. Simulation and experimental results on mobile robots are presented to validate the performance of the hierarchical control framework for multi-robot systems.

Route-dependent switch between hierarchical and egalitarian strategies in pigeon flocks.

The mechanisms that underlie fascinating inter-individual interactions among animal groups have attracted increasing attention from biologists, physicists, and system scientists. There are two well-known types of interaction patterns: hierarchical and egalitarian. In the former type, individuals follow their leaders, whereas they follow their neighbors in the latter. Using high-resolution spatiotemporal data derived from the free flights of a flock of pigeons, we show that pigeon flocks actually adopt a mode that switches between the two aforementioned strategies. To determine its flight direction, each pigeon tends to follow the average of its neighbors while moving along a smooth trajectory, whereas it switches to follow its leaders when sudden turns or zigzags occur. By contrast, when deciding how fast to fly, each pigeon synthesizes the average velocity of its neighbors. This switching mechanism is promising for possible industrial applications in multi-robot system coordination, unmanned vehicle formation control, and other areas.

Modeling and Distributed Implementation of Synchronization and Coordination in Multi-Robot Systems

This paper deals with control system design and implementation problems encountered in multiple robot systems. A systematic method of constructing hierarchical net models is described for their direct implementation such that the net is translated into the detailed net by stepwise refinements from the highest task specification level to the lowest machine control level. Basic Petri nets are extended as a prototyping tool for expressing real-time control of robotic systems based on command response concept. The hierarchical and distributed coordinators are introduced to perform the synchronization and coordination of the robots and other machines in the system. The proposed method allows a direct coding of the inter-task cooperation from the net specification and can be implemented using off–the-shelf real-time executives.

Partial state consensus for networks of second-order dynamic agents

This paper addresses the partial state consensus problem of multi-agent systems with second-order agent dynamics and proposes an asynchronous distributed consensus protocol for the case with switching interaction topology, time-varying delays and intermittent information transmission. “Partial state consensus” means reaching an agreement asymptotically with each other on part, but not all, of each individual’s states, where the concerned states usually cannot be decoupled from the other ones. Partial state consensus has its broad applications in the coordination of multi-robot systems, distributed task management, and distributed estimation for sensor networks, etc. This paper assumes that position-like states are the only detectable information transmitted over the network and velocity-like states are the key quantities of interest, which are required to be equalized. We first give the asynchronous distributed protocol based on the delayed position-like state information and then provide its convergence result with respect to velocity-like states. It is shown that if the union of the interaction topology across the time interval with a given length always contains a spanning tree, then the proposed protocol will solve the partial state (velocity-like state) consensus problem asymptotically.

Special issue on swarm robotics

Swarm robotics is a new approach to the coordination of multi-robot systems. In contrast with traditional multi-robot systems which use centralised or hierarchical control and communication systems in order to coordinate robots’ behaviours, swarm robotics adopts a decentralised approach in which the desired collective behaviours emerge from the local interactions between robots and their environment. Such emergent or self-organised collective behaviours are inspired by, and in some cases modelled on, the swarm intelligence observed in social insects. The potential for swarm robotics is considerable. Any task in which physically distributed objects need to be explored, surveyed, collected, harvested, rescued, or assembled into structures is a potential real-world application for swarm robotics. The key advantage of the swarm robotics approach is robustness, which manifests itself in a number of ways. Firstly, because a swarm of robots consists of a number of relatively simple and typically homogeneous robots, which are not pre-assigned to specific roles or tasks within the swarm, then the swarm can self-organise or dynamically re-organise the way individual robots are deployed. Secondly, and for the same reasons, the swarm approach is highly tolerant to the failure of individual robots. Thirdly, the fact that control is completely decentralised means that there is no common-mode failure point or vulnerability in the swarm. Indeed, it could be said that the high level of robustness evident in robotic swarms comes for free in the sense that it is intrinsic to the swarm robotics approach, which contrasts with the high engineering cost of fault tolerance in conventional robotic systems. The realisation of the potential of swarm robotics requires the solution of a number of very challenging problems. Firstly, in algorithm design: swarm roboticists face the problem of designing both the physical morphology and behaviours of the individual robots such that when those robots interact with each other and their environment, the desired overall collective behaviours will emerge. At present there are no principled approaches to the design of low-level behaviours for a given desired collective behaviour. Secondly, in implementation

Adaptive force-motion control of coordinated robots interacting with geometrically unknown environments

Most studies on adaptive coordination of multi-robot systems assume exact knowledge of system kinematics and deal only with dynamic uncertainties. However, many industrial applications involve tasks in which a multi-robot system interacts with geometrically unknown environments. In this paper, we consider a multi-robot system grasping a rigid object in contact with a geometrically unknown surface. The proposed adaptive hybrid force-motion controller guarantees asymptotic tracking of desired motion and force trajectories while ensuring exact identification of constraint Jacobian matrix without persistency of excitation condition. The control signal is smooth and does not depend on contact force derivative. The proposed adaptive controller is robustified against environmental friction and nonparametric uncertainty in environment geometry. Simulation examples are presented to illustrate the results.

Multirobot Systems: A Classification Focused on Coordination

Multirobot systems (MRS) are, nowadays, an important research area within robotics and artificial intelligence and a growing number of systems have recently been presented in the literature. Since application domains and tasks that are faced by MRS are of increasing complexity, the ability of the robots to cooperate can be regarded as a fundamental feature. In this paper, we present a survey of the recent work in the area by specifically examining the forms of cooperation and coordination realized in the MRS. In particular, we propose a new taxonomy for classification of the approaches to coordination in MRS and we describe some systems, which we consider representative in our taxonomy. We finally discuss the outcomes of our analysis and try to highlight future trends of the research on MRS.