Autonomous Mobile Agents Research Articles

SWARM INTELLIGENCE EMBEDDED DATA MINING FOR PRECISION AGRICULTURE ADVANCEMENTS

The present study investigates the potential of Swarm Intelligence (SI) in driving breakthroughs in Precision Agriculture (PA). It focuses on the research of mining techniques to uncover novel insights and developments in the field of PA. Social informatics (SI) is an academic discipline that focuses on the examination of collective behaviour within both herbal and synthetic structures. In order to gather, analyse, and synthesise information, SI utilises self-sufficient mobile devices known as Autonomous Mobile Agents (AMAs). These entities refer to robotic and computational frameworks that engage in mutual interaction, facilitating the examination of collective intelligence. This essay examines the potential impact of utilising the System of International Units (SI) on enhancing the accuracy and precision of commodity production and control in the field of production agriculture (PA). It also highlights the existing advancements that have been achieved in this regard. This analysis examines possible uses of Swarm Intelligence in the Public Administration (PA) industry, as well as the challenges that need to be solved in order to enhance the efficiency and accuracy of PA operations.

Active-sensing-based decentralized control of autonomous mobile agents for quick and smooth collision avoidance.

There is an increasing demand for multi-agent systems in which each mobile agent, such as a robot in a warehouse or a flying drone, moves toward its destination while avoiding other agents. Although several control schemes for collision avoidance have been proposed, they cannot achieve quick and safe movement with minimal acceleration and deceleration. To address this, we developed a decentralized control scheme that involves modifying the social force model, a model of pedestrian dynamics, and successfully realized quick, smooth, and safe movement. However, each agent had to observe many nearby agents and predict their future motion; that is, unnecessary sensing and calculations were required for each agent. In this study, we addressed this issue by introducing active sensing. In this control scheme, an index referred to as the "collision risk level" is defined, and the observation range of each agent is actively controlled on this basis. Through simulations, we demonstrated that the proposed control scheme works reasonably while reducing unnecessary sensing and calculations.

Detection of Static and Mobile Targets by an Autonomous Agent with Deep Q-Learning Abilities.

This paper addresses the problem of detecting multiple static and mobile targets by an autonomous mobile agent acting under uncertainty. It is assumed that the agent is able to detect targets at different distances and that the detection includes errors of the first and second types. The goal of the agent is to plan and follow a trajectory that results in the detection of the targets in a minimal time. The suggested solution implements the approach of deep Q-learning applied to maximize the cumulative information gain regarding the targets’ locations and minimize the trajectory length on the map with a predefined detection probability. The Q-learning process is based on a neural network that receives the agent location and current probability map and results in the preferred move of the agent. The presented procedure is compared with the previously developed techniques of sequential decision making, and it is demonstrated that the suggested novel algorithm strongly outperforms the existing methods.

Emergence of bipartite flocking behavior for Cucker-Smale model on cooperation-competition networks with time-varying delays

This paper explores the collective behavior of bipartite flocking for a set of autonomous mobile agents based on Cucker-Smale update rules on directed cooperation-competition networks. In our model, cooperative or competitive degree between neighbouring agents is set by a nonlinear function of the communication distance between agents, which is called weight function, and further the influence of communication delays on the system stability and the final distance between agents is analyzed. With the help of related conclusions about sub-stochastic matrices, a sufficient condition relying on the topology structure, weight functions and initial states is established to guarantee the realization of bipartite flocking behavior. In the end the effectiveness of dynamic results is verified through a numerical example.

A Locust-Inspired Model of Collective Marching on Rings.

We study the collective motion of autonomous mobile agents in a ringlike environment. The agents’ dynamics are inspired by known laboratory experiments on the dynamics of locust swarms. In these experiments, locusts placed at arbitrary locations and initial orientations on a ring-shaped arena are observed to eventually all march in the same direction. In this work we ask whether, and how fast, a similar phenomenon occurs in a stochastic swarm of simple locust-inspired agents. The agents are randomly initiated as marching either clockwise or counterclockwise on a discretized, wide ring-shaped region, which we subdivide into k concentric tracks of length n. Collisions cause agents to change their direction of motion. To avoid this, agents may decide to switch tracks to merge with platoons of agents marching in their direction. We prove that such agents must eventually converge to a local consensus about their direction of motion, meaning that all agents on each narrow track must eventually march in the same direction. We give asymptotic bounds for the expected time it takes for such convergence or “stabilization” to occur, which depends on the number of agents, the length of the tracks, and the number of tracks. We show that when agents also have a small probability of “erratic”, random track-jumping behavior, a global consensus on the direction of motion across all tracks will eventually be reached. Finally, we verify our theoretical findings in numerical simulations.

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.

Multiple-Valued Logic Modelling for Agents Controlled via Optical Networks

The methods of data verification are discussed, which are intended for the distant control of autonomous mobile robotic agents via networks, combining optical data links. The problem of trust servers is considered for position verification and position-based cryptography tasks. In order to obtain flexible quantum and classical verification procedures, one should use the collective interaction of agents and network nodes, including some elements of the blockchain. Multiple-valued logic functions defined within discrete k-valued Allen–Givone algebra are proposed for the logically linked list of entries and the distributed ledger, which can be used for distant data verification and breakdown restoration in mobile agents with the help of partner network nodes. A distributed ledger scheme involves the assigning by distant partners of random hash values, which further can be used as keys for access to a set of distributed data storages, containing verification and restoration data. Multiple-valued logic procedures are simple and clear enough for high-dimensional logic modelling and for the design of combined quantum and classical protocols.

Design of a Digital 3D Model of Transport-Technological Environment of Open-Pit Mines Based on the Common Use of Telemetric and Geospatial Information.

This article is devoted to the issues of processing and analysis of heterogeneous information related to the functioning of mining transport equipment, which becomes available for analysis within the framework of modern technological operations control systems in open-pit mines. These issues are very relevant to robotized technological operations. The paper gives a brief overview of the modern landscape of the autonomous haulage systems management problems, the features of the platform approach to solving the problem of managing unmanned transport and technological processes in open pits are considered. The concept of an agent-based approach to the modeling of an open-pit mining is described in detail on the basis of the interaction of three systems: technical, infrastructural–technological, and geostructural. Some features of the developed platform architecture integration of heterogeneous information are discussed. The principles of information integration are considered in detail when constructing a dynamic 3D model (digital twin) of infrastructure and technological system elements using large arrays of telemetric data. The results of building digital models of open-pit technological roads are presented. The resulting models are comparatively analyzed in the process of optimizing of the interaction of technical autonomous mobile agents and elements of technological infrastructure.

Measuring the Vulnerability of a Multi-Agent Pathfinding Solution

Multi-agent pathfinding is the problem of finding a non-interfering paths for a set of agents, such that if the agents follow these paths then each agent will reach its desired destination. Recent years have shown tremendous advances in this field, with optimal and suboptimal algorithms that are able to plan paths for over 100 agents in reasonable time. However, autonomous mobile agents are prime targets for cyber-security attacks, where an adversary may take control over an agent to disrupt the agents execution of their plan. This threat raises two questions. The first question is how much damage can an agent do if it does not follow its plan. The second question is how can one plan a-priori to be as robust as possible to such cyber-attacks. In this work, We provide an answer to both questions. To compute the maximal amount of damage that an adversary agent can do, we define a corresponding graph search problem and solve this problem with A*. Then, we provide a very simple method to choose a solution that is robust to such damages. We demonstrate both algorithms in simulation over standard multi-agent pathfinding domains.

Collective multi agent deployment for wireless sensor network maintenance

In this paper, we study the problem of wireless sensor network (WSN) maintenance using a team of physical autonomous mobile agents. The agents are deployed in the area of the WSN in such a way that would minimize the time it takes them to reach a failed sensor and repair it. The team must constantly optimize its collective deployment to account for occupied agents. The objective is to define the optimal deployment and task allocation strategy, that minimize the solution cost. The solution cost is a linear combination of the weighted sensors’ downtime, the agents’ traveling distance, and penalties incurred due to unrepaired sensors within a certain time limit.Our proposed solution algorithms are inspired by research in the field of computational geometry and the design of our algorithms is based on state of the art approximation algorithms for the classical problem of facility location.We empirically compare and analyze the performance of several proposed algorithms. The sensitivity of the algorithms’ performance to the following parameters is analyzed: agents to sensors ratio, sensors’ sparsity, frequency and distribution of failures, repair duration, repair capacity, and communication limitations. Our results demonstrate that: (i) cooperation enhances the team’s performance by orders of magnitude, (ii) k-Median based deployment algorithm provides up to 30% improvement in downtime, (iii) k-Center based deployment incurs 10% fewest penalties, and (iv) k-Centroid based deployment is most efficient in terms of minimizing the overall costs, with up to 21% lower cost than the next best algorithm.

Algorithms for coordination of autonomous underwater drones searching for a hidden object when no long-range communication is allowed

The paper is devoted to comparison of the efficiency of information exchange by autonomous mobile agents when searching in a limited coverage area. The special feature of the problem is to consider the case of operation within the prohibition of usage of radio, light, and acoustic communication channels at a great distance, as well as without surfacing. The paper compares the following algorithms for the work of groups of autonomous robots, based on a preliminary division of area into sectors and survey of robots in their sectors using the “breadth-first search” method.

Minimal Deterministic Traversable Vertex Labelling of Infinite Square Grid Graph

Automata walking on graphs are a mathematical formalization of autonomous mobile agents with limited memory operating in discrete environments. Under this model a broad area of studies of the behaviour of automata in labyrinths arose and intensively developing last decades (a labyrinth is an embedded directed graph of special form). Research in this regard received a wide range of applications, for example, in the problems of image analysis and navigation of mobile robots. Automata operating in labyrinths can distinguish directions, that is, they have a compass. This paper deals with the problem of constructing square grid graph vertex labelling thanks to which a finite automaton without a compass can walk on graph in any arbitrary direction. The automaton looking over neighbourhood of the current vertex and may travel to some neighbouring vertex selected by its label. In this paper, we propose a minimal deterministic traversable vertex labelling that satisfies the required property. A labelling is said to be deterministic if all vertices in closed neighbourhood of every vertex have different labels. In previous works we have proved that minimal deterministic traversable vertex labelling of square grid graph uses labels of five different types. In this paper we prove that a collective of one automaton and three pebbles can construct this labelling on initially unlabelled infinite square grid graph. We consider pebbles as automata of the simplest form, whose positions are completely determined by the remaining automata of the collective.

Compacting oblivious agents on dynamic rings.

In this paper we investigate dynamic networks populated by autonomous mobile agents. Dynamic networks are networks whose topology can change continuously, at unpredictable locations and at unpredictable times. These changes are not considered to be faults, but rather an integral part of the nature of the system. The agents can autonomously move on the network, with the goal of solving cooperatively an assigned common task. Here, we focus on a specific network: the unoriented ring. More specifically, we study 1-interval connected dynamic rings (i.e., at any time, at most one of the edges might be missing). The agents move according to the widely used Look–Compute–Move life cycle, and can be homogenous (thus identical) or heterogenous (agents are assigned colors from a set of c > 1 colors). For identical agents, their goal is to form a compact segment, where agents occupy a continuous part of the ring and no two agents occupy the same node: we call this the Compact Configuration Problem. In the case of agents with colors, called the Colored Compact Configuration Problem, the goal is to group agents such that each group is formed by all agents having the same color, it occupies a continuous segment of the network, and groups of agents having different colors occupy distinct areas of the network. In this paper we determine the necessary conditions to solve both proposed problems. For all solvable cases, we provide algorithms for both the monochromatic and the colored version of the compact configuration problem. All our algorithms work even for the simplest model where agents have no persistent memory, no communication capabilities and do not agree on a common orientation within the network. To the best of our knowledge this is the first work on the compaction problem in a dynamic network.

Robot Evacuation on a Line Assisted by a Bike

Two robots and a bike are initially placed at the origin of an infinite line. The robots are modelled as autonomous mobile agents whose communication capabilities are either in the wireless or face-to-face model, while the bike neither can move nor communicate on its own. Thus, the bike is not autonomous but rather requires one of the robots to ride it. An exit is placed on the line at distance d from the origin; the distance and direction of the exit from the origin is unknown to the robots. Only one robot may ride the bike at a time and the goal is to evacuate from the exit in the minimum time possible as measured by the time it takes the last robot to exit. The robots can maintain a constant walking speed of 1, but when riding the bike they can maintain a constant speed v>1 (same for both robots). We develop algorithms for the evacuation of the two robots from the unknown exit and analyze the evacuation time defined as the time it takes the second robot to evacuate. In the wireless model we present three algorithms: in the first the robots move in opposite direction with max speed, in the second with a specially selected “optimal” speed, and in the third the robot imitates the biker (i.e., robot riding the bike). We also give three algorithms in the Face-to-Face model: in the first algorithm the robot pursues the biker, in the second the robot and the biker use zig-zag algorithms with specially chosen expansion factors, and the third algorithm establishes a sequence of specially constructed meeting points near the exit. In either case, the optimality of these algorithms depends on v>1. We also discuss lower bounds.

Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams

This work is about mission planning in teams of mobile autonomous agents. We consider tasks that are spatially distributed, non-atomic, and provide an utility for integral and also partial task completion. Agents are heterogeneous, therefore showing different efficiency when dealing with the tasks. The goal is to define a system-level plan that assigns tasks to agents to maximize mission performance. We define the mission planning problem through a model including multiple sub-problems that are addressed jointly: task selection and allocation, task scheduling, task routing, control of agent proximity over time. The problem is proven to be NP-hard and is formalized as a mixed integer linear program (MILP). Two solution approaches are proposed: one heuristic and one exact method. Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. To support performance scalability and to allow the effective use of the model when online continual replanning is required, a decentralized and fully distributed architecture is defined top-down from the MILP model. Decentralization drastically reduces computational requirements and shows good scalability at the expenses of only moderate losses in performance. Lastly, we illustrate the application of the mission planning framework in two demonstrators. These implementations show how the framework can be successfully integrated with different platforms, including mobile robots (ground and aerial), wearable computers, and smart-phone devices.

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.

Synchronization-based symmetric circular formations of mobile agents and the generation of chaotic trajectories

The self-organization of multiple autonomous mobile agents is a trending topic nowadays with applications in robotics, aerospace engineering, and satellite formations. We investigate a model of particles with coupled-oscillators dynamics focusing on the particular case of agents grouping in symmetric clusters while moving in concentric circular trajectories. Our results reveal that certain regions of the parameter space are more suitable for the onset of such clusters. Additionally, we study the effects of adding and removing agents from already formed clusters, prescribe a strategy to properly switch from one formation to another, and finally introduce an approach to obtain chaotic almost-circular trajectories and symmetric clusters with non-overlapping particles.

On the fast delivery problem with one or two packages

We study two problems where k autonomous mobile agents are initially located on distinct nodes of a weighted graph with n nodes and m edges. Each agent has a predefined velocity and can only move along the edges of the graph. The first problem is to deliver one package from a source node to a destination node. The second is to simultaneously deliver two packages, each from its source node to its destination node. These deliveries are achieved by the collective effort of the agents, which can carry and exchange a package among them. For one package, we propose an O(knlog⁡n+km) time algorithm for computing a delivery schedule that minimizes the delivery time. For two packages, we show that the problem of minimizing the maximum or the sum of the delivery times is NP-hard for arbitrary agent velocities, but polynomial-time solvable for agents with equal velocity.

Method for analyzing the stability of information transfer between unmanned aerial vehicles in the formation

The use of a formation consisting of adaptive autonomous mobile agents allows solving a wide range of tasks that are often beyond the capabilities of individual agents. A multi-agent formation is a complex high-order dynamic system, so analyzing the stability of such a system is a complex task. At present, the problem of estimating the stability of a formation formed by substantially nonlinear high-order agents with variable dynamic parameters is not sufficiently considered. This task is particularly important for a formation that is affected by complex unstable environmental conditions, in particular for the formation of unmanned aerial vehicles (UAVs). A method for analyzing the stability of formations of nonlinear agents with different types and orders of transfer function has been developed for studying information exchange in UAV networks. The new approach is based on the use of the Popov frequency criterion and the piecewise linear approximation of the hodograph. A computational experiment was performed to analyze the stability of a formation with transfer functions of various types and orders from the 1st to the 10th. The conducted studies revealed a significant difference in the calculated boundary coefficients of formation stability in the linear and nonlinear modes, which confirms the need to analyze the nonlinear stability under the influence of strong destabilizing influences on the formation.

Information Transmission Bounds Between Moving Terminals

In networks of mobile autonomous agents, e.g. for data acquisition, we may wish to maximize data transfer or to reliably transfer a minimum amount of data, subject to quality of service or energy constraints. These requirements can be guaranteed through both offline node design/specifications and online trajectory/communications design. Regardless of the distance between them, for a stationary point-to-point transmitter-receiver pair communicating across a single link under average power constraints, the total data transfer is unbounded as time tends to infinity. In contrast, we show that if the transmitter/receiver is moving at any constant speed away from each other, then the maximum transmittable data is bounded. Although general closed-form expressions as a function of communication and mobility profile parameters do not yet exist, we provide closed-form expressions for particular cases, such as ideal free space path loss. Under more general scenarios we instead give lower bounds on the total transmittable information across a single link between mobile nodes.