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An Adaptive -Based Formation Control for Multirobot Systems  [PDF]
Faridoon Shabani,Bijan Ranjbar,Ali Ghadamyari
ISRN Robotics , 2013, DOI: 10.5402/2013/192487
Abstract: We describe a decentralized formation problem for multiple robots, where an formation controller is proposed. The network of dynamic agents with external disturbances and uncertainties are discussed in formation problems. We first describe how to design social potential fields to obtain a formation with the shape of a polygon. Then, we provide a formal proof of the asymptotic stability of the system, based on the definition of a proper Lyapunov function and technique. The advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, while applicability on a group of any autonomous systems with -degrees of freedom. Finally, simulation results are demonstrated for a multiagent formation problem of a group of six robots, illustrating the effective attenuation of approximation error and external disturbances, even in the case of agent failure or leader tracking. 1. Introduction All around the world, nature presents examples of collective behavior in groups of insects, birds, and fishes. This behavior has produced sophisticated functions of the group that cannot be achieved by individual members [1, 2]. Therefore, the research on the coordination of robotic swarms has attracted considerable attention. Taking the advantages of distributed sensing and actuation, a robotic swarm can perform some cooperative tasks such as moving a large object that is usually not executable by a single robot [3–7]. Applications about the analysis and design of robotic swarms included autonomous unmanned aerial vehicles, congestion control of communication networks, and distributed sensor networks autonomous, and so forth [1, 2, 8–10]. In general, a robotic formation problem is defined as the organization of a swarm of agents into a particular shape in a 2D or 3D space [8]. This kind of control strategy can be applied into several different fields. For example, in the industrial field, this formation control strategy can be applied to a group of Automated Guided Vehicles (AGVs) moving in a warehouse for goods delivery. The main idea is to make a group of AGVs cooperatively deliver a certain amount of goods, moving in a formation. The creation of a formation with the desired shape is useful to precisely constrain the action zone of the AGVs, thus reducing the chance of collisions with other entities (e.g., human guided vehicles). In the literature, many different approaches to formation control can be found. The main existing approaches can be divided into two categories: centralized [11] and distributed
An Adaptive Particle Swarm Optimization Algorithm for Distributed Search and Collective Cleanup in Complex Environment  [PDF]
Yi Cai,Zhutian Chen,Jun Li,Qing Li,Huaqing Min
International Journal of Distributed Sensor Networks , 2013, DOI: 10.1155/2013/560579
Abstract: Distributed coordination is critical for a multirobot system in collective cleanup task under a dynamic environment. In traditional methods, robots easily drop into premature convergence. In this paper, we propose a Swarm Intelligence based algorithm to reduce the expectation time for searching targets and removing. We modify the traditional PSO algorithm with a random factor to tackle premature convergence problem, and it can achieve a significant improvement in multi-robot system. It performs well even in a obstacle environment. The proposed method has been implemented on self-developed simulator for searching task. The simulation results demonstrate the feasibility, robustness, and scalability of our proposed method compared to previous methods. 1. Introduction Searching and cleaning targets in an unknown dynamic environment through multirobot system have numerous real world applications [1], such as hazardous waste cleanup [2], urban search and rescue [3], surveillance systems, and monitoring in military combat environment. Distributed multirobot systems demand group coherence and group competence [4]. Due to its robustness, flexibility, and reliability, the distributed coordination is desirable for multirobot systems under dynamic environment [5, 6]. Therefore, the main challenge for multirobot systems is to develop intelligent robots which can adapt their behaviors based on interaction with the environment and other robots, so as to become more proficient in their tasks in new situations [7, 8]. Recently, when tackling the problem of how to organize the large scale robots efficiently without high cost under dynamic and unknown environment, more and more researchers adopt bioinspired coordination methods. Swarm robotics provides a new approach for coordination of multirobot systems consisting of large number of relatively simple robots. The term “Swarm Intelligence” is inspired by an understanding of the decentralized mechanisms that underlie the organization of natural swarms such as ants, bees, fish, wolves, and even humans. Typical research in swarm-based robotic systems can be classified to a few domains, which include biological inspiration [9], parallel searching [10, 11], coordinated movement [12], pattern formation [13, 14], and mapping and localization [15]. All of these systems consist of multiple robots or embodied simulated robots acting autonomously based on their own decisions. To stimulate the colonial organization, such as bird flock and ant colony, Swarm Intelligence theory has been put forward. Particle Swarm Optimization and Ant
Minefield Mapping Using Cooperative Multirobot Systems  [PDF]
Alaa Khamis,Asser ElGindy
Journal of Robotics , 2012, DOI: 10.1155/2012/698046
Abstract: This paper presents a team-theoretic approach to cooperative multirobot systems. The individual actions of the robots are controlled by the Belief-Desire-Intention model to endow the robots with the know-how needed to execute these actions deliberately. The cooperative behaviors between the heterogeneous robots are governed by the Team-Log theory to endow all the robots in the team with the know-how-to-cooperate and determine the team members’ commitments to each other despite their different types, properties, and goals. The proposed approach is tested for validity with the real life problem of minefield mapping. Different minefield sweeping strategies are studied to control the mobility of the mobile sweepers within the minefield in order to maximize the area coverage and improve picture compilation capability of the multirobot system. 1. Introduction Developing a robust and cooperative team of robots capable of solving complex tasks is an interesting area of research that attracts many researchers nowadays. Achieving robust and productive cooperation between various system components is inspired by different domains such as biology, artificial life, psychology, and cognitive science in order to build artificially cooperative intelligent systems. Cooperation is defined in [1] as a purposive positive interference of agents to further the achievement of a common goal or goals compatible with their own. To achieve this effective cooperation in multirobot systems (MRS), the robots must have know-how for solving simple problems in an autonomous way and a know-how-to-cooperate by which agents can share common interests and interact with each other to solve complex problems cooperatively. In recent years, scientific community has seen a great number of research works dedicated to cooperative multirobot systems and their applications in different areas such as search and rescue [2, 3], distributed surveillance [4], communication relaying [5], agriculture [6], sorting [7], emergency services [8], and landmine detection [9]. Minefield reconnaissance and mapping is one of the most promising applications of cooperative multirobot systems. In the context of humanitarian demining, cooperative multirobot systems can be beneficial for deminers, civilians, and government. The design of an accurate sensor may reduce the amount of time needed to determine whether a landmine exists, but does not increase the safety of the deminer. Since the safety issues during the eradication process are of great concern, the use and integration of cheap and simple mobile sweepers in
Development and Simulation of a Task Assignment Model for Multirobot Systems  [PDF]
B.B.Biswal,B.B.Choudhury
International Journal of Engineering , 2007,
Abstract: Multirobot systems (MRS) hold the promise of improved performance and increased fault tolerance for large-scale problems. A robot team can accomplish a given task more quickly than a single agent by executing them concurrently. A team can also make effective use of specialists designed for a single purpose rather than requiring that a single robot be a generalist. Multirobot coordination, however, is a complex problem. An empirical study is described in the present paper that sought general guidelines for task allocation strategies. Different task allocation strategies are identified, and demonstrated in the multi-robot environment. A simulation study of the methodology is carried out in a simulated grid world. The results show that there is no single strategy that produces best performance in all cases, and that the best task allocation strategy changes as a function of the noise in the system. This result is significant, and shows the need for further investigation of task allocation strategies.
Consensus Formation Control for a Class of Networked Multiple Mobile Robot Systems  [PDF]
Long Sheng,Ya-Jun Pan,Xiang Gong
Journal of Control Science and Engineering , 2012, DOI: 10.1155/2012/150250
Abstract: A consensus-based formation control for a class of networked multiple mobile robots is investigated with a virtual leader approach. A novel distributed control algorithm is designed based on the Lyapunov method and linear matrix inequality (LMI) technique for time delay systems. A multiple Lyapunov Krasovskii functional candidate is proposed for investigating the sufficient conditions to linear control gain design for the system with constant time delays. Simulation results as well as experimental studies on Pioneer 3 series mobile robots are shown to verify the effectiveness of the proposed approach. 1. Introduction Embedded computational resources in autonomous robotic vehicles are becoming more abundant and have enabled improved operational effectiveness of cooperative robotic systems in civilian and military applications. Compared to autonomous robotic vehicles that operate single tasks, cooperative teamwork has greater efficiency and operational capability. Multirobotic vehicle systems have many potential applications, such as platooning of vehicles in urban transportation, the operation of the multiple robots, autonomous underwater vehicles, and formation of aircrafts in military affairs [1–3]. The study of group behaviors for multirobot systems is the main objective of the work. Group cooperative behavior signifies that individuals in the group share a common objective and action according to the interest of the whole group. Group cooperation can be efficient if individuals in the group coordinate their actions well. Each individual can coordinate with other individuals in the group to facilitate group cooperative behavior in two ways, named local coordination and global coordination. For the local coordination, individuals react only to other individuals that are close, such as fish engaged in a school. For the global coordination, each individual can directly coordinate its act with every other individual in the group. Due to communication constraints, most researchers are interested primarily in group cooperation problems where the coordination occurs locally [4–6]. Cooperative control of multirobotic vehicle systems brings us significant theoretical [7–9] and practical challenges. For example, the research objective is defined based on a system of some subsystems rather than a single system; the effects caused by the communication constraints should be considered and how to design coordination strategies so that coordination will result in a group cooperation [10, 11]. As a concrete example of cooperative control, the formation control of
Decentralized Discrete-Time Formation Control for Multirobot Systems  [cached]
E. G. Hernandez-Martinez,J. J. Flores-Godoy,G. Fernandez-Anaya
Discrete Dynamics in Nature and Society , 2013, DOI: 10.1155/2013/746713
Abstract:
Capacity Performance of Adaptive Receive Antenna Subarray Formation for MIMO Systems  [cached]
Theofilakos Panagiotis,Kanatas Athanasios G
EURASIP Journal on Wireless Communications and Networking , 2007,
Abstract: Antenna subarray formation is a novel RF preprocessing technique that reduces the hardware complexity of MIMO systems while alleviating the performance degradations of conventional antenna selection schemes. With this method, each RF chain is not allocated to a single antenna element, but instead to the complex-weighted and combined response of a subarray of elements. In this paper, we derive tight upper bounds on the ergodic capacity of the proposed technique for Rayleigh i.i.d. channels. Furthermore, we study the capacity performance of an analytical algorithm based on a Frobenius norm criterion when applied to both Rayleigh i.i.d. and measured MIMO channels.
Capacity Performance of Adaptive Receive Antenna Subarray Formation for MIMO Systems  [cached]
Panagiotis Theofilakos,Athanasios G. Kanatas
EURASIP Journal on Wireless Communications and Networking , 2007, DOI: 10.1155/2007/56471
Abstract: Antenna subarray formation is a novel RF preprocessing technique that reduces the hardware complexity of MIMO systems while alleviating the performance degradations of conventional antenna selection schemes. With this method, each RF chain is not allocated to a single antenna element, but instead to the complex-weighted and combined response of a subarray of elements. In this paper, we derive tight upper bounds on the ergodic capacity of the proposed technique for Rayleigh i.i.d. channels. Furthermore, we study the capacity performance of an analytical algorithm based on a Frobenius norm criterion when applied to both Rayleigh i.i.d. and measured MIMO channels.
The networked seceder model: Group formation in social and economic systems  [PDF]
Andreas Gronlund,Petter Holme
Physics , 2003, DOI: 10.1103/PhysRevE.70.036108
Abstract: The seceder model illustrates how the desire to be different than the average can lead to formation of groups in a population. We turn the original, agent based, seceder model into a model of network evolution. We find that the structural characteristics our model closely matches empirical social networks. Statistics for the dynamics of group formation are also given. Extensions of the model to networks of companies are also discussed.
Adaptive mesh computation of polycrystalline pattern formation using a renormalization-group reduction of the phase-field crystal model  [PDF]
Badrinarayan P. Athreya,Nigel Goldenfeld,Jonathan A. Dantzig,Michael Greenwood,Nikolas Provatas
Physics , 2007, DOI: 10.1103/PhysRevE.76.056706
Abstract: We implement an adaptive mesh algorithm for calculating the space and time dependence of the atomic density field during materials processing. Our numerical approach uses the systematic renormalization-group formulation of the phase field crystal model to provide the underlying equations for the complex amplitude of the atomic density field--a quantity that is spatially uniform except near topological defects, grain boundaries and other lattice imperfections. Our algorithm is a hybrid formulation of the amplitude equations, combining Cartesian and polar decompositions of the complex amplitude. We show that this approach leads to an acceleration by three orders of magnitude in model calculations of polycrystalline domain formation in two dimensions.
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