• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.390-395
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• 2012

This paper describes an implementation of automatic mutual localization of swarm robots using a particle filter. Each robot determines the location of the other robots using wireless sensors. The measured data will be used for determination of the movement method of the robot itself. It also affects the other robots' self-arrangement into formations such as circles and lines. We discuss the problem of a circle formation enclosing a target that moves. This method is the solution for enclosing an invader in a circle formation based on mutual localization of the multi-robot without infrastructure. We use trilateration, which does require knowing the value of the coordinates of the reference points. Therefore, specifying the enclosure point based on the number of robots and their relative positions in the coordinate system. A particle filter is used to improve the accuracy of the robot's location. The particle filter is operates better for mutual location of robots than any other estimation algorithms. Through the experiments, we show that the proposed scheme is stable and works well in real environments.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.370-388
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• 2015

The localization of multi-agents, such as people, animals, or robots, is a requirement to accomplish several tasks. Especially in the case of multi-robotic applications, localization is the process for determining the positions of robots and targets in an unknown environment. Many sensors like GPS, lasers, and cameras are utilized in the localization process. However, these sensors produce a large amount of computational resources to process complex algorithms, because the process requires environmental mapping. Currently, combination multi-robots or swarm robots and sensor networks, as mobile sensor nodes have been widely available in indoor and outdoor environments. They allow for a type of efficient global localization that demands a relatively low amount of computational resources and for the independence of specific environmental features. However, the inherent instability in the wireless signal does not allow for it to be directly used for very accurate position estimations and making difficulty associated with conducting the localization processes of swarm robotics system. Furthermore, these swarm systems are usually highly decentralized, which makes it hard to synthesize and access global maps, it can be decrease its flexibility. In this paper, a simple pyramid RAM-based Neural Network architecture is proposed to improve the localization process of mobile sensor nodes in indoor environments. Our approach uses the capabilities of learning and generalization to reduce the effect of incorrect information and increases the accuracy of the agent's position. The results show that by using simple pyramid RAM-base Neural Network approach, produces low computational resources, a fast response for processing every changing in environmental situation and mobile sensor nodes have the ability to finish several tasks especially in localization processes in real time.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.1
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• pp.10-15
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• 2009

With the development of techniques, robots are getting smaller, and the number of robots needed for application is greater and greater. How to coordinate large number of autonomous robots through local interactions has becoming an important research issue in robot community. Swarm Robot Systems (SRS) is a system that independent autonomous robots in the restricted environments infer their status from pre-assigned conditions and operate their jobs through the cooperation with each other. In the SRS, a robot contains sensor part to percept the situation around them, communication part to exchange information, and actuator part to do a work. Especially, in order to cooperate with other robots, communicating with other robots is one of the essential elements. Because Bluetooth has many advantages such as low power consumption, small size module package, and various standard protocols, it is rated as one of the efficient communicating technologies which can apply to small-sized robot system. In this paper, we will develop Bluetooth communicating system for autonomous robots. And we will discuss how to construct and what kind of procedure to develop the communicating system for group behavior of the SRS under intelligent space.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.429-434
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• 2013

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.725-730
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• 2012

In this paper, we propose the localization algorithm for the cooperative behavior of the swarm robots based on WSN (Wireless Sensor Network). The proposed method is as follows: First, we measure positions of the L-bot (Leader robot) and F-bots (Follower robots) by using the APIT (Approximate Point In Triangle) and the RSSI (Received Signal Strength Indication). Second, we measure relative positions of the F-bots against the pre-measured position of the L-bot by using trilateration. Then, to revise a position error caused by noise of the wireless signal, we use the particle filter. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.806-816
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• 2011

Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.130-134
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• 2012

In this paper, we propose a space partitioning technique for swarm robots by using the Centroidal Voronoi Tessellation. The proposed method consists of two parts such as space partition and collision avoidance. The space partition for searching a given space is carried out by a density function which is generated by some accidents. The collision avoidance is implemented by the potential field method. Finally, the numerical experiments show the effectiveness and feasibility of the proposed method.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.349-354
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• 2014

A maze-escaping method with cooperating work of robots alongside one another will be proposed in this paper. Educational robots can communicate each other using Zigbee; however, they can't solve problems together due to their lack of arithmetic function. The robots walk upright controlled by a motion program; furthermore, they recognize an intersection or a dead-end in the use of distant sensors with sending data and receiving commands from the central control system. The maze-search algorithms were modified so that all robots can effectively navigate the maze.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.416-422
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• 2013

This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, $A^*$ algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. $A^*$ algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.9-16
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• 2023

Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.