Multi-agent Mobile Research Articles

Real-Time Multi-Agent Mobile Robot based on A Client-Server Model

A client-server network is one of the most important topics in a computer network. In this work, a real-time computer control system is designed based on the Client-Server Model for a Multi-Agent Mobile Robot System (CSM-MAMRS) and is applied to a building that consists of (N) floors and uses one mobile robot on each floor that has specific actions in different types of environments. The new proposed CSM-MAMRS consists of four layers. The first stage manages the network communication for each agent. The second stage solves the major problems of path planning by using a proposed hybrid algorithm that combines the Rapidly Exploring Random Tree Star (RRT*) and the Particle Swarm Optimization (PSO) algorithms in order to provide the shortest and smoothest path with collision avoidance between the starting and the target points in a static and dynamic robot environments are used.. In the third stage, a velocity planner controller is based on an inverse kinematic mobile robot model. In the fourth stage, the Hypertext Transfer Protocol HTTP is used to send velocity values to real mobile robots via the Wireless Network Control Administration. The simulation results and experimental works successfully achieved to significant improvement in real-time when using three missions of three mobile robots on different static map floors in the building. The maximum tracking pose errors for three robots in the static enviormnets are 0.39 cm, 0.02 cm, 0.32 cm respectively, but the maximum tracking pose error in the dynamic environments are 2.94 cm and 2.8 cm only for two mobile robots along the maximum distance of 250 cm. Index Terms— Real-time computer control, Mobile robot, Multi-agent system, Path planning algorithms.

Full-Field Vibration Response Estimation from Sparse Multi-Agent Automatic Mobile Sensors Using Formation Control Algorithm.

In structural vibration response sensing, mobile sensors offer outstanding benefits as they are not dedicated to a certain structure; they also possess the ability to acquire dense spatial information. Currently, most of the existing literature concerning mobile sensing involves human drivers manually driving through the bridges multiple times. While self-driving automated vehicles could serve for such studies, they might entail substantial costs when applied to structural health monitoring tasks. Therefore, in order to tackle this challenge, we introduce a formation control framework that facilitates automatic multi-agent mobile sensing. Notably, our findings demonstrate that the proposed formation control algorithm can effectively control the behavior of the multi-agent systems for structural response sensing purposes based on user choice. We leverage vibration data collected by these mobile sensors to estimate the full-field vibration response of the structure, utilizing a compressive sensing algorithm in the spatial domain. The task of estimating the full-field response can be represented as a spatiotemporal response matrix completion task, wherein the suite of multi-agent mobile sensors sparsely populates some of the matrix's elements. Subsequently, we deploy the compressive sensing technique to obtain the dense full-field vibration complete response of the structure and estimate the reconstruction accuracy. Results obtained from two different formations on a simply supported bridge are presented in this paper, and the high level of accuracy in reconstruction underscores the efficacy of our proposed framework. This multi-agent mobile sensing approach showcases the significant potential for automated structural response measurement, directly applicable to health monitoring and resilience assessment objectives.

Distributed strategy selection: A submodular set function maximization approach

Joint utility-maximization problems for multi-agent systems often should be addressed by distributed strategy-selection formulation. Constrained by discrete feasible strategy sets, these problems are broadly formulated as NP-hard combinatorial optimization problems. In many cases, these problems can be cast as constrained submodular set function maximization problems, which also belong to the NP-hard domain of problems. A prominent example is the problem of multi-agent mobile sensor dispatching over a discrete domain. This paper considers a class of submodular optimization problems that consist of maximization of a monotone and submodular set function subject to a partition matroid constraint over a group of networked agents that communicate over a connected undirected graph. We work with the value oracle model. Consequently, the only access of the agents to the utility function is through a black box that returns the utility function value given a specific strategy set. We propose a distributed suboptimal polynomial-time algorithm that enables each agent to obtain its respective strategy via local interactions with its neighboring agents. Our solution is a fully distributed gradient-based algorithm using the submodular set functions’ multilinear extension followed by a distributed stochastic Pipage rounding procedure. This algorithm results in a strategy set that when the team utility function is evaluated at the worst case, the utility function value is in 1c(1−e−c−O(1/T)) of the optimal solution with c being the curvature of the submodular function. An example demonstrates our results.

An enhanced searching strategy for multi-agent mobile applications

Multi-agent mobile applications play an essential role in mobile applications and have attracted more and more researchers' attention. Previous work has always focused on multi-agent applications with perfect information. Researchers are usually based on human-designed rules to provide decision-making searching services. However, existing methods for solving perfect-information mobile applications cannot be directly applied to imperfect-information mobile applications. Here, we take the Contact Bridge, a multi-agent application with imperfect information, for the case study. We propose an enhanced searching strategy to deal with multi-agent applications with imperfect information. We design a self-training bidding system model and apply a Recurrent Neural Network (RNN) to model the bidding process. The bridge system model consists of two parts, a bidding prediction system based on imitation learning to get a contract quickly and a visualization system for hands understanding to realize regular communication between players. Then, to dynamically analyze the impact of other players' unknown hands on our final reward, we design a Monte Carlo sampling algorithm based on the bidding system model (BSM) to deal with imperfect information. At the same time, a double-dummy analysis model is designed to efficiently evaluate the results of sampling. Experimental results indicate that our searching strategy outperforms the top rule-based mobile applications.

Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model.

More details about human movement patterns are needed to evaluate relationships between daily travel and malaria risk at finer scales. A multiagent mobility simulation model was built to simulate the movements of villagers between home and their workplaces in 2 townships in Myanmar. An agent-based model (ABM) was built to simulate daily travel to and from work based on responses to a travel survey. Key elements for the ABM were land cover, travel time, travel mode, occupation, malaria prevalence, and a detailed road network. Most visited network segments for different occupations and for malaria-positive cases were extracted and compared. Data from a separate survey were used to validate the simulation. Mobility characteristics for different occupation groups showed that while certain patterns were shared among some groups, there were also patterns that were unique to an occupation group. Forest workers were estimated to be the most mobile occupation group, and also had the highest potential malaria exposure associated with their daily travel in Ann Township. In Singu Township, forest workers were not the most mobile group; however, they were estimated to visit regions that had higher prevalence of malaria infection over other occupation groups. Using an ABM to simulate daily travel generated mobility patterns for different occupation groups. These spatial patterns varied by occupation. Our simulation identified occupations at a higher risk of being exposed to malaria and where these exposures were more likely to occur.

Distributed Encirclement Points Deployment of Autonomous Mobile Multi-Agents Based on Finite-Time Consensus

In the many-to-one pursuit-evasion game, autonomous mobile multi-agents can effectively improve the probability of successful hunting by achieving the cooperative encirclement to the target from multiple directions. To solve the encirclement points deployment, a distributed control protocol is proposed based on finite-time consensus. Firstly, the encirclement points deployment is formulated as the coverage control problem on a circle. The presented distributed control protocol can realize uniform coverage on the circle, i.e., optimal encirclement around the target. Secondly, by introducing the strategy of time-varying feedback gain, the convergence rate of closed-loop system turns into finite-time consensus from asymptotical consensus, such that the efficiency of the deployment is improved greatly. Finally, numerical simulations are carried out to verify the effectiveness of the presented distributed control protocols.

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.

Performance analysis of hierarchical location management system for mobile-multi-agent system

Location management of a Mobile Agent (MA) is necessary for a Mobile Agent System (MAS), in which many significant services are accomplished using MA communications that require specific location information. This paper gives the performance analysis of a Hierarchical Location Management System (HLMS) for mobile Multi Agent System (MUS) with the objectives to reduce the search and update cost. This work also discusses a mailbox-based approach to provide communication among MAs. Mailbox is a data structure which is used to store the messages for MAs. There are two different communication mechanisms (jump and full migration) with mailbox have been used. In jump migration MA's mailbox always resides at the local router and in full migration MA always carries its mailbox with it at the host it is executing. For jump migration MA periodically checks its mailbox to get the message. HLMS has been modelled using the timed Coloured Petri Net (CPN) tool. Performance of HLMS is then observed for identified parameters such as Trip Time (TT), Migration Rate (MR), Search Rate (SR), Network Overhead (ND) and Communication Time (COT). Simulation results show that HLMS can locate the MAs in a fault free environment but TT and ND decrease as intra-region MR increases.

Performance analysis of hierarchical location management system for mobile-multi-agent system

Location management of a Mobile Agent (MA) is necessary for a Mobile Agent System (MAS), in which many significant services are accomplished using MA communications that require specific location information. This paper gives the performance analysis of a Hierarchical Location Management System (HLMS) for mobile Multi Agent System (MUS) with the objectives to reduce the search and update cost. This work also discusses a mailbox-based approach to provide communication among MAs. Mailbox is a data structure which is used to store the messages for MAs. There are two different communication mechanisms (jump and full migration) with mailbox have been used. In jump migration MA's mailbox always resides at the local router and in full migration MA always carries its mailbox with it at the host it is executing. For jump migration MA periodically checks its mailbox to get the message. HLMS has been modelled using the timed Coloured Petri Net (CPN) tool. Performance of HLMS is then observed for identified parameters such as Trip Time (TT), Migration Rate (MR), Search Rate (SR), Network Overhead (ND) and Communication Time (COT). Simulation results show that HLMS can locate the MAs in a fault free environment but TT and ND decrease as intra-region MR increases.

Large-scale multi-agent mobility simulations on a GPU: towards high performance and scalability

This paper describes the ongoing development of GEMSim, a GPU-based mobility simulator that is systematically designed for generic large-scale networks and population samples. In order to fully exploit the benefits of the massively parallel architecture of GPU hardware, in GEMSim, the structure of the overall simulation loop, the organisation of memory transactions on GPU, data structures on both GPU and host, and the learning process are considered carefully. First results for a large-scale scenario of Switzerland are presented, and show that a whole simulation loop of GEMSim is more than 12 times faster than MATSim, and mobility simulations run up to 58 times faster in GEMSim compared to MATSim. Thus, this GPU-based mobility simulator makes practical advanced traffic simulation and forecasting tools more accessible to planners and decision makers.

Finite-Time Sliding Mode Controller Design for Formation Control of Multi-Agent Mobile Robots

Finite-Time Sliding Mode Controller Design for Formation Control of Multi-Agent Mobile Robots

MARS: An Educational Environment for Multiagent Robot Simulations

Undergraduate robotics students often find it difficult to design and validate control algorithms for teams of mobile robots. This is mainly due to two reasons. First, very rarely, educational laboratories are equipped with large teams of robots, which are usually expensive, bulky, and difficult to manage and maintain. Second, robotics simulators often require students to spend much time to learn their use and functionalities. For this purpose, a simulator of multiagent mobile robots namedMARShas been developed within the Matlab environment, with the aim of helping students to simulate a wide variety of control algorithms in an easy way and without spending time for understanding a new language. Through this facility, the user is able to simulate multirobot teams performing different tasks, from cooperative to competitive ones, by using both centralized and distributed controllers. Virtual sensors are provided to simulate real devices. A graphical user interface allows students to monitor the robots behaviour through an online animation.

Simulating social influences on sustainable mobility shifts for heterogeneous agents

Greenhouse gas emissions by vehicle traffic should be reduced not only through innovations in automotive technology but also through a modal shift to sustainable transport. The modal shift to sustainable transport corresponding to the transport policy, as well as the purchase of clean energy vehicles (CEV) is regarded as the mobility shift. Therefore, both service improvement for sustainable transport modes, such as the bus rapid transit system, and economic incentive policies are considered in transport policy. Conversely, as the local community influences decisions on mobility shift, the estimation of CO2 emissions should describe local interaction. Particularly, heterogeneity of local interaction should be described in the modeling of the mobility shift. Therefore, the mobility shift is modeled to incorporate heterogeneity and local interaction to estimate the effect of transport policies in reducing CO2 emissions. The research question is how much do heterogeneity and local interaction influence mobility shift with the policy for sustainable transport. A multi-agent mobility shift simulation model that considers heterogeneity and local interaction is developed. For this purpose, the stated preference for mode change and purchase CEV policies is investigated via a questionnaire survey. The proposed multi-agent simulation model includes the decision process of the agent regarding mobility shift, the social influence process in the social network, and the CO2 emission process. The decision process for commuting mode is modeled using the hierarchical Bayesian method mainly to describe the heterogeneity of the influence of the local mode share. The day-to-day dynamics of commuting mode choice and the purchase of CEVs corresponding to the transport policy are estimated using the proposed multi-agent simulation model. The results confirm that the heterogeneity of influence on social conformity should be considered in the modeling of modal shift as both conformity effects and non-conformity effects are observed. However, the assumption of homogeneous commuters might cause estimates that are too high, since the heterogeneity of commuters decreases the share of the sustainable transport mode. Furthermore, the green tax policy is confirmed to be suitable for maximizing the reduction rate of CO2 emissions, as pricing based on fuel consumption maximizes reduction efficiency.

Automatic Synthesis of Control for Multi-Agent Systems with Dynamic Constraints

The paper solves the problem of automatic synthesis of a control system. The result of the control synthesis is a synthesizing control function that depends on the current state of the object and provides the optimal control with the best functional value from any initial point of some initial domain. A network operator method is used to solve the problem. We apply the proposed approach for control synthesis of a robotic team. The main challenge with such multi-agent mobile systems is to provide control meeting inter agent dynamic constraints. The method's performance is demonstrated through simulations on a team of two mobile robots performing a parking task.

CronoClock: A Multiagent Mobile Model to Assist Drivers in Park Zones

We present a model based on multiagent environment to help users of park zones. A multiagent system is built to communicate the different roles and devices belonging to the system. The result is a model that assists the different users in their payments and identifies the vehicle plate by image recognition and NFC (Near Field Communication) technology. An evaluation of the system is provided to know the efficiency of the model.

An Accelerated Resource Utilization in Autonomous Stochastic Mobile Multi-Agents

This paper describes how to coordinate autonomous mobile multi-agents, whose agents stochastically move over a finite resource consisting of cells in accordance with transition probabilities. We assume there are interactions or coordination among agents such that (1) each agent cannot move to a destination cell occupied by agents more than the agents of a current cell and (2) their agents have time-lag. Then it is ideal that every cell is always occupied by agents, because of the efficient use of resources, and it is desirable to be the fewest expected number of cells not occupied by agents. The first result shows that the resource utilization of accelerated mobile multi-agents with appropriate average moving speed becomes higher than the resource utilization of mobile multi-agents without average moving speed. Then the resource utilization can be accelerated to maximum by giving appropriate moving speed. The second result shows that there are the best moving speed of system-specific optimum to utilize the resources of autonomous stochastic mobile multi-agents.

From Exploring to Optimal Path Planning: Considering Error of Navigation in Multi-Agent Mobile Robot Domain

From Exploring to Optimal Path Planning: Considering Error of Navigation in Multi-Agent Mobile Robot Domain

Development of Reactive Control Strategy for Multi-Agent Mobile Robotics System

Multi–agent system is one the most popular research interests in robotics nowadays. Imagine for a swarm of robots, what kind of intelligence can we build now? This question arises from emulating biological systems. How is it that colonies of small ants can work together to perform a difficult task that single ant cannot do it alone? How might collections of simple robots aid us in human endeavours? By examining these questions, one of the common characteristics shared by each agent is in agent simplicity. Simplicity in control means that the robots are provided with direct commands in order to execute the action. It doesn’t need to gather all information from various sensors to plan its action like deliberative control which is also known as sensors fusion that clearly required a lot of computational time and also the mapping that its produces might not valid at the time when changes occurs between the time it gathers the information and the time it plans its actions. Instead, intelligence will arise when these simple agents work together to perform some complex task cooperatively. By examining the major control architectures available in robotics area, subsumption–based reactive control architecture gives the tools as required. Priority–based scheme is used in arbitration level to select which behaviour to run. In this paper decentralised reactive control architecture was used to justify the communication based simple control architecture can perform complex task like carrying load and navigate. Key words: Multi-agent system; reactive control architecture; control algorithm

Distributed-Controlled Multiagent Mobile Platform with Digital Actuation Concept for Space Applications

This paper describes an architecture for a multiagent robotic system that consists of a number of identical units. The homogeneous units are mechanically connected to construct a mobile platform named a “multiagent transportation (MAT) system.” Every unit has its local controller that communicates only with its adjacent units. This basic configuration of supervisorless structure affirmatively confines the dependence of each unit to a local area, and therefore any unit can be removed from or added into any part of a MAT system regardless of the timing and without disturbing the performance of the whole system. This flexibility of configuration significantly contributes to easy maintenance of units, such as battery charging or hot-replacing for faulty units. Utilizing this flexibility, MAT systems are able to adapt to a variety of tasks including transportation application and to target objects of various shapes and range of mass. These characteristics of MAT systems are the strong advantages for mobile rob...

Consensus and Synchronization in Delayed Networks of Mobile Multi-agents

AbstractThe stability of consensus algorithms in networks of mobile multi-agents with transmission delays is investigated. The movements of agents are modeled by the random waypoint (RWP) model. Thus, the communication topology is modeled as induced by a homogeneous Markov chain. It is found that, under several conditions, the stability dynamics are dramatically influenced by the delay patterns. In the case where self-links exist and are instantaneous, consensus is reached if the expectation of the graph topology has a spanning tree; in the other case where the self-links have delays and only integer delays with certain patterns are possible, the algorithm does not reach consensus but instead synchronizes at a periodic trajectory, whose period depends on the delay patterns. The dynamics in the absence of self-links exhibit similar phenomena. The theoretical results are verified in a network of RWP mobile agents.