Showing papers on "Ant robotics published in 2013"
TL;DR: This paper analyzes the literature from the point of view of swarm engineering and proposes two taxonomies: in the first taxonomy, works that deal with design and analysis methods are classified; in the second, works according to the collective behavior studied are classified.
Abstract: Swarm robotics is an approach to collective robotics that takes inspiration from the self-organized behaviors of social animals. Through simple rules and local interactions, swarm robotics aims at designing robust, scalable, and flexible collective behaviors for the coordination of large numbers of robots. In this paper, we analyze the literature from the point of view of swarm engineering: we focus mainly on ideas and concepts that contribute to the advancement of swarm robotics as an engineering field and that could be relevant to tackle real-world applications. Swarm engineering is an emerging discipline that aims at defining systematic and well founded procedures for modeling, designing, realizing, verifying, validating, operating, and maintaining a swarm robotics system. We propose two taxonomies: in the first taxonomy, we classify works that deal with design and analysis methods; in the second taxonomy, we classify works according to the collective behavior studied. We conclude with a discussion of the current limits of swarm robotics as an engineering discipline and with suggestions for future research directions.
1,405 citations
TL;DR: It is believed that swarm robotics designers must embrace heterogeneity if they ever want swarm robotics systems to approach the complexity required of real-world systems.
Abstract: Swarm robotics systems are characterized by decentralized control, limited communication between robots, use of local information, and emergence of global behavior. Such systems have shown their potential for flexibility and robustness [1]-[3]. However, existing swarm robotics systems are by and large still limited to displaying simple proof-of-concept behaviors under laboratory conditions. It is our contention that one of the factors holding back swarm robotics research is the almost universal insistence on homogeneous system components. We believe that swarm robotics designers must embrace heterogeneity if they ever want swarm robotics systems to approach the complexity required of real-world systems.
362 citations
TL;DR: The current research on the swarm robotic algorithms are presented in detail, including cooperative control mechanisms in swarm robotics for flocking, navigating and searching applications.
282 citations
TL;DR: An overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems, together with a discussion of the future swarm robotics in real world applications.
Abstract: Swarm robotics is a field of multi-robotics in which large number of robots are coordinated in a distributed and decentralised way. It is based on the use of local rules, and simple robots compared to the complexity of the task to achieve, and inspired by social insects. Large number of simple robots can perform complex tasks in a more efficient way than a single robot, giving robustness and flexibility to the group. In this article, an overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems. A review of different research works and experimental results, together with a discussion of the future swarm robotics in real world applications completes this work.
187 citations
TL;DR: A review of recent activities in swarm robotic research is presented, and existing literature in the field is analyzed to determine how to get closer to a practical swarm robotic system for real world applications.
Abstract: We present a review of recent activities in swarm robotic research, and analyse existing literature in the field to determine how to get closer to a practical swarm robotic system for real world applications. We begin with a discussion of the importance of swarm robotics by illustrating the wide applicability of robot swarms in various tasks. Then a brief overview of various robotic devices that can be incorporated into swarm robotic systems is presented. We identify and describe the challenges that should be resolved when designing swarm robotic systems for real world applications. Finally, we provide a summary of a series of issues that should be addressed to overcome these challenges, and propose directions for future swarm robotic research based on our extensive analysis of the reviewed literature.
170 citations
22 Jul 2013
TL;DR: This work considers non-transparent unit-disc robots in an asynchronous setting with vision as the only means of coordination and robots only make local decisions and develops a distributed algorithm that solves the problem for any number of fat robots.
Abstract: We revisit the problem of gathering autonomous robots in the plane. In particular, we consider non-transparent unit-disc robots (i.e., fat) in an asynchronous setting with vision as the only means of coordination and robots only make local decisions. We use a state-machine representation to formulate the gathering problem and develop a distributed algorithm that solves the problem for any number of fat robots. The main idea behind the algorithm is to enforce the robots to reach a configuration in which all the following hold:(i) The robots' centers form a convex hull in which all robots are on the convex hull's boundary;(ii) Each robot can see all other robots;(iii) The configuration is connected: every robot touches another robot and all robots form together a connected formation.We show that starting from any initial configuration, the fat robots eventually reach such a configuration and terminate yielding a solution to the gathering problem.
102 citations
01 Jan 2013
TL;DR: In this paper, the authors present an analysis based on both reliability modelling and experimental trials of a case study swarm performing team work, in which failures are deliberately induced, and conclude that future large scale swarm systems will need a new approach to achieving high levels of fault tolerance.
Abstract: This paper challenges the common assumption that swarm robotic systems are robust and scalable by default. We present an analysis based on both reliability modelling and experimental trials of a case study swarm performing team work, in which failures are deliberately induced. Our case study has been carefully chosen to represent a swarm task in which the overall desired system behaviour is an emergent property of the interactions between robots, in order that we can assess the fault tolerance of a self-organising system. Our findings show that in the presence of worst-case partially failed robots the overall system reliability quickly falls with increasing swarm size. We conclude that future large scale swarm systems will need a new approach to achieving high levels of fault tolerance.
52 citations
06 May 2013
TL;DR: This paper proposes a strategy for transporting a tall, and potentially heavy, object to a goal using a large number of miniature mobile robots, and makes no use of communication between the robots.
Abstract: This paper proposes a strategy for transporting a tall, and potentially heavy, object to a goal using a large number of miniature mobile robots. The robots move the object by pushing it. The direction in which the object moves is controlled by the way in which the robots distribute themselves around its perimeter - if the robots dynamically reallocate themselves around the section of the object's perimeter that occludes their view of the goal, the object will eventually be transported to the goal. This strategy is fully distributed, and makes no use of communication between the robots. A controller based on this strategy was implemented on a swarm of 12 physical e-puck robots, and a systematic experiment with 30 randomized trials was performed. The object was successfully transported to the goal in all the trials. On average, the path traced by the object was about 8.4% longer than the shortest possible path.
43 citations
TL;DR: Experimental results on computer-generated and real-world networks show the capability of the adaptive approach based on ant colony clustering to discover communities in a complex network to successfully detect community structures.
Abstract: Community structure detection in complex networks has been intensively investigated in recent years. In this paper, we propose an adaptive approach based on ant colony clustering to discover communities in a complex network. The focus of the method is the clustering process of an ant colony in a virtual grid, where each ant represents a node in the complex network. During the ant colony search, the method uses a new fitness function to percept local environment and employs a pheromone diffusion model as a global information feedback mechanism to realize information exchange among ants. A significant advantage of our method is that the locations in the grid environment and the connections of the complex network structure are simultaneously taken into account in ants moving. Experimental results on computer-generated and real-world networks show the capability of our method to successfully detect community structures.
37 citations
TL;DR: The paper describes the various techniques for the robot path planning using the Ant colony Algorithm and provides the brief comparison of the three techniques described in the paper.
Abstract: Path planning problem, is a challenging topic in robotics. Indeed, a significant amount of research has been devoted to this problem in recent years. The ant colony optimization algorithm is another approach to solve this problem. Each ant drops a quantity of artificial pheromone on every point that the ant passes through. This pheromone simply changes the probability that the next ant becomes attracted to a particular grid point. The techniques described in the paper adapt a global attraction term which guides ants to head toward the destination point. The paper describes the various techniques for the robot path planning using the Ant colony Algorithm. The paper also provides the brief comparison of the three techniques described in the paper.
36 citations
TL;DR: The results show that this approach outperforms ad-hoc extensions of state-of-the-art cost-based coordination methods and that the approach is able to efficiently coordinate teams of heterogeneous robots and to consider symbolic actions.
Abstract: The efficient coordination of a team of heterogeneous robots is an important requirement for exploration, rescue, and disaster recovery missions. In this paper, we present a novel approach to target assignment for heterogeneous teams of robots. It goes beyond existing target assignment algorithms in that it explicitly takes symbolic actions into account. Such actions include the deployment and retrieval of other robots or manipulation tasks. Our method integrates a temporal planning approach with a traditional cost-based planner. The proposed approach was implemented and evaluated in two distinct settings. First, we coordinated teams of marsupial robots. Such robots are able to deploy and pickup smaller robots. Second, we simulated a disaster scenario where the task is to clear blockades and reach certain critical locations in the environment. A similar setting was also investigated using a team of real robots. The results show that our approach outperforms ad-hoc extensions of state-of-the-art cost-based coordination methods and that the approach is able to efficiently coordinate teams of heterogeneous robots and to consider symbolic actions.
TL;DR: This paper focusses on the development of a customised mapping and exploration task for a heterogeneous ensemble of mobile robots, which consists of computationally powerful robots at the upper level and limited capability robots (workers) at the lower levels.
TL;DR: This paper presents a comprehensive study on hardware architecture and several other important aspects of modular swarm robots, such as: self-reconfigurability, self-replication, and self-assembly.
Abstract: Swarm robotics is one the most fascinating and new research areas of recent decades, and one of the grand challenges of robotics is the design of swarm robots that are self-sufficient. This can be crucial for robots exposed to environments that are unstructured or not easily accessible for a human operator, such as the inside of a blood vessel, a collapsed building, the deep sea, or the surface of another planet. In this paper, we present a comprehensive study on hardware architecture and several other important aspects of modular swarm robots, such as: self-reconfigurability, self-replication, and self-assembly. The key factors in designing and building a group of swarm robots are cost and miniaturization with robustness, flexibility and scalability. In robotics intelligence, self-assembly and self reconfigurability are among the most important characteristics as they can add additional capabilities and functionality to swarm robots. Simulation and model design for swarm robotics is highly complex and expensive, especially when attempting to model the behavior of large swarm robot groups.
12 Jun 2013
TL;DR: A swarm of robotic fish is developed that enables us to examine collective behaviors in fish shoals and first results of the analysis of behavioral experiments are shown.
Abstract: Biomimetic robots can be used to analyze social behavior through active interference with live animals. We have developed a swarm of robotic fish that enables us to examine collective behaviors in fish shoals. The system uses small wheeled robots, moving under a water tank. The robots are coupled to a fish replica inside the tank using neodymium magnets. The position of the robots and each fish in the swarm is tracked by two cameras. The robots can execute certain behaviors integrating feedback from the swarm’s position, orientation and velocity. Here, we describe implementation details of our hardware and software and show first results of the analysis of behavioral experiments.
01 Dec 2013
TL;DR: Using computer simulations, it is shown that the Lévy walk-like searching strategy can maximize the group foraging efficiency of the swarm robots using pheromone trails (mimicking ant Group foraging), as well as maximize individual searching area.
Abstract: This paper describes an implementation of Levy walk (or Levy flight) to pheromone communicating swarm robots. Levy flight is a special class of random walk in which the step length distribution is given by power law distribution. Levy flight is known to maximize the efficiency of resource searches in uncertain environments. Using computer simulations, we show that the Levy walk-like searching strategy can maximize the group foraging efficiency of the swarm robots using pheromone trails (mimicking ant group foraging), as well as maximize individual searching area. The Levy walk was achieved by adjusting the probability per unit time with which an individual robot moves forward (otherwise it turns to right, to left, and reverse). We discuss the effect of swarming on optimal parameter values of Levy walk. Optimization of individual searching strategies should be studied further, both in swarm robots and real organisms.
09 Jul 2013
TL;DR: A nature-inspired cooperative method to reduce the operating costs of the foraging swarm robots through simulation experiments that employs a behavioral model of honey bee swarm to improve the energy efficiency in collecting crops or minerals.
Abstract: Operating swarm robots has the virtues of improved performance, fault tolerance, distributed sensing, and so on. Although, high overall system cost is the main barrier in managing a system of foraging swarm robots. Moreover, its control algorithm should be scalable and reliable as the foraging (search) spaces become wider. This paper analyzes a nature-inspired cooperative method to reduce the operating costs of the foraging swarm robots through simulation experiments. The method employs a behavioral model of honey bee swarm to improve the energy efficiency in collecting crops or minerals. Experiments demonstrate the effectiveness of the approach.
23 Jun 2013
TL;DR: A set of simulations of a swarm of robots running the decentralized asynchronous particle swarm optimization, bacterial foraging optimization and ant colony optimization algorithms was used to investigate the effectiveness of the divergence operator in odor source declaration.
Abstract: This paper explores the use of the divergence operator for odor source declaration in swarm-based algorithms A set of simulations of a swarm of robots running the decentralized asynchronous particle swarm optimization, bacterial foraging optimization and ant colony optimization algorithms was used to generate multiple wind and odor biased vector fields to investigate the effectiveness of the divergence operator in odor source declaration A set of real world experiments were also performed using the same swarm algorithms on a controlled environment to ascertain if the divergence operator can also be used on real data The sparse gas sensor data acquired by the robots was interpolated using the Nadaraya-Watson estimator by means of a wind and odor biased kernel before the application of the divergence Results show that the divergence operator excels at odor source declaration
13 Oct 2013
TL;DR: An improved ant colony system algorithm for path planning of mobile robots is proposed by considering two main aspects, including continuous tuning of a setting parameter and the establishment of new mechanisms for pheromone updating, which can be significantly enhanced in comparison to the traditional ACS algorithms.
Abstract: Although traditional ant colony system (ACS) has the ability of fast convergence, it tends to find local optima. To solve this problem, this paper proposes an improved ant colony system algorithm for path planning of mobile robots by considering two main aspects, including continuous tuning of a setting parameter and the establishment of new mechanisms for pheromone updating. As a result, the ability of global searching of the improved ACS can be significantly enhanced in comparison to the traditional ACS algorithms in deriving an optimal path for mobile robots. Simulation results show the proposed approach has a better performance in terms of shortest distance, mean distance, and successful rate of the optimal paths than those obtained by the traditional ACS algorithms.
01 Jan 2013
TL;DR: This paper compares three deployment strategies characterised by nominal computation, memory, communication and sensing requirements, and finds that a novel strategy that controls the density of flying robots is most promising in reducing swarm energy costs while maintaining rapid search times.
Abstract: A major challenge in swarm robotics is efficiently deploying robots into unknown environments, minimising energy and time costs. This is especially important with small aerial robots which have extremely limited flight autonomy. This paper compares three deployment strategies characterised by nominal computation, memory, communication and sensing requirements, and hence are suitable for flying robots. Energy consumption is decreased by reducing unnecessary flight following two premises: 1) exploiting environmental information gathered by the robots; 2) avoiding diminishing returns and reducing interference between robots. Using a 3- D dynamics simulator we examine energy and time metrics, and also scalability effects. Results indicate that a novel strategy that controls the density of flying robots is most promising in reducing swarm energy costs while maintaining rapid search times. Furthermore, we highlight the energy-time tradeoff and the importance of measuring both metrics, and also the significance of electronics power in calculating total energy consumption, even if it is small relative to locomotion power.
TL;DR: Simulation results under an ideal environment show that APO is a feasible and effective when applied to swarm robotic search for target with global sense.
Abstract: Swarm robotics is an important research area of swarm intelligence. Swarm robots searching potential target provides a better way in victim search or rescue operations in some disaster scenarios. This paper uses artificial physics optimisation APO algorithm as the modelling tool for solving swarm robots searching problem. Firstly, viewed as an individual moving in a closed two-dimensional workspace, each robot is abstracted as one order inertial element. Further, the model of swarm robots search for target with global sense based on APO algorithm is given, in which the virtual force law among robots is constructed through referring the attraction-repulsion rule of APO. Simulation results under an ideal environment show that APO is a feasible and effective when applied to swarm robotic search for target with global sense.
01 Jan 2013
TL;DR: This brief paper focuses on the robot swarm that achieves cooperative transportation making use of ethanol as a substantial artificial pheromone and proposes a swarm system with a newly developed algorithm that enables cooperative transportation of real robots.
Abstract: Ants communicate with each other using pheromones, and their society is highly sophisticated. When foraging, they transport cooperatively with interplay of forces. The swarm is robust against changes in internal state, and shows flexibility in dealing with external problems. In this brief paper, we focus on the robot swarm that achieves cooperative transportation making use of ethanol as a substantial artificial pheromone.We also propose a swarm system with a newly developed algorithm that enables cooperative transportation of real robots. They will transport food to the nest analogous to the behaviour of a swarm of ants. Emphasis will be placed on the systematic task solution process.We present a number of experiments demonstrating the robustness and flexibility of the system and also confirming the effectiveness of the algorithm.
TL;DR: The term service robots was invented to show robotics technologies and applications in nonmanufacturing areas to represent the new trend away from the narrow focus of the robotics community on the control of the robotic manipulators.
Abstract: We may think that robots were invented to serve humans. Consequently, what is the disparity between the terms service robots and service robotics? Although this is a valid point, to distinguish from the initial wide usage of robots in manufacturing, the term service robotics was invented to show robotics technologies and applications in nonmanufacturing areas. The term service robots was intended to highlight emerging markets for the new types of robots. This was the motivation behind initiating the Service Robots Technical Committee (TC) within the IEEE Robotics and Automation Society (RAS) in 1995. During the same period, the term intelligent robots appeared in the literature (see [1]) to represent the new trend away from the narrow focus of the robotics community on the control of the robotic manipulators.
TL;DR: A swarm of ant robotic agents (robots with limited sensing, communication, computational and memory resources) form a visual representation of distributed hazardous substances within an environment dominated by diffusion processes using a decentralized approach.
21 Jun 2013
TL;DR: Experimental results show that the new algorithm can provide desirable safety path under the complex situation, which contains dense obstacles or many concave blocks, as well as computational time can meet the requirement of practically applications.
Abstract: An enhanced ant colony optimization algorithm is proposed. The search deadlock is ruled out through modifying both initial environment pheromone and state transition probability. The roundabout of trajectory is improved by combining deterministic search with stochastic search. Experimental results show that the new algorithm can provide desirable safety path under the complex situation, which contains dense obstacles or many concave blocks, as well as computational time can meet the requirement of practically applications.
02 Sep 2013
TL;DR: This work uses a genetic algorithm to optimize behavior in a team of simulated robots that mimic foraging ants, then transfer the evolved behaviors into physical iAnt robots, demonstrating the utility of employing evolutionary methods to optimize the performance of distributed robot teams in unknown environments.
Abstract: Evolutionary algorithms can adapt the behavior of individuals to maximize the fitness of cooperative multi-agent teams. We use a genetic algorithm (GA) to optimize behavior in a team of simulated robots that mimic foraging ants, then transfer the evolved behaviors into physical iAnt robots. We introduce positional and resource detection error models into our simulation to characterize the empirically-measured sensor error in our physical robots. Physical and simulated robots that live in a world with error and use parameters adapted specifically for an error-prone world perform better than robots in the same error-prone world using parameters adapted for an error-free world. Additionally, teams of robots in error-adapted simulations collect resources at the same rate as the physical robots. Our approach extends state-of-theart biologically-inspired robotics, evolving high-level behaviors that are robust to sensor error and meaningful for phenotypic analysis. This work demonstrates the utility of employing evolutionary methods to optimize the performance of distributed robot teams in unknown environments.
01 Jan 2013
TL;DR: This paper addresses the safe navigation of multiple nonholonomic mobile robots in shared areas using the virtual leader principle together with a local linear controller.
Abstract: This paper addresses the safe navigation of multiple nonholonomic mobile robots in shared areas Obstacle avoidance for mobile robots is performed by artificial potential fields and special traffic rules In addition, the behavior of mobile robots is optimized by particle swarm optimization (PSO) The control of non-holonomic vehicles is performed using the virtual leader principle together with a local linear controller
01 Dec 2013
TL;DR: A swarm of robots that interacts like a swarm of insects, cooperating with each other accurately and efficiently is achieved, attempting to simulate the way a collective of animals behave, as a single cognitive entity.
Abstract: This work focuses on the application of Swarm Intelligence to a problem of garbage and recycling collection using a swarm of robots. Computational algorithms inspired by nature, such as Particle Swarm Optimization (PSO) and Ant Colony Optimization, have been successfully applied to a range of optimization problems. Our idea is to train a number of robots to interact with each other, attempting to simulate the way a collective of animals behave, as a single cognitive entity. What we have achieved is a swarm of robots that interacts like a swarm of insects, cooperating with each other accurately and efficiently. We describe two different PSO topologies implemented, showing the obtained results, a comparative evaluation, and an explanation of the rationale behind the choices of topologies that enhanced the PSO algorithm. Moreover, we describe and implement an Ant Colony Optimization (ACO) approach that presents an unusual grid implementation of a robot physical simulation. Hence, generating new concepts and discussions regarding the necessary modifications for the algorithm towards an improved performance. The ACO is then compared to the PSO results in order to choose the best algorithm to solve the proposed problem.
01 Dec 2013
TL;DR: A hybrid technique for the control of swarms of robots, based on Particle Swarm Optimisation (PSO) and Consensus algorithms, is presented in this paper to combine PSO's adaptation skills for the exploration of unknown environments and the ability of the Consensus to maintain a group of robots in a desired formation.
Abstract: A hybrid technique for the control of swarms of robots, based on Particle Swarm Optimisation (PSO) and Consensus algorithms, is presented in this paper. The purpose of this technique is to combine PSO's adaptation skills for the exploration of unknown environments and the ability of the Consensus to maintain a group of robots in a desired formation. The overall control scheme is designed in a distributed form. This fact is particularly suitable for the control of a swarm of robots where one or more agents can experience temporary or permanent communication disconnection from the group, due to various reasons (e.g. malfunctions). Simulations are presented to illustrate the proposed technique.
24 Jun 2013
TL;DR: A distributed control algorithm to dynamic task allocation in a swarm robotics environment where each robot that integrates the swarm must run the algorithm periodically in order to control the underlying actions and decisions is proposed.
Abstract: This paper proposes a distributed control algorithm to im- plement dynamic task allocation in a swarm robotics environment. In this context, each robot that integrates the swarm must run the algorithm periodically in order to control the underlying actions and decisions. The algorithm was implemented and extensively tested. The corresponding performance and effectiveness are promising.
TL;DR: Simulation results under an ideal environment show that APO algorithm is feasible and effective when applied to swarm robotic search for target with local sense.
Abstract: Swarm robots search is an effective method for rescue operation and victim search in some disaster. Due to robot's limited sensing capability in practical applications, time-varying sense domain is introduced to denote robot's dynamic neighbourhood structure. Artificial physics optimisation APO algorithm is used to construct the model of swarm robots system. Then, the model of swarm robotic search for target with local sense based on APO is proposed, which include robot's mass function designing, force definition and the cooperative control strategy description. Simulation results under an ideal environment show that APO algorithm is feasible and effective when applied to swarm robotic search for target with local sense.