• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.5-11
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• 2010

An adaptive formation control approach is proposed for nonhonolomic multiple mobile robots considering unknown slipping and skidding. It is assumed that unknown slipping and skidding effects are bounded by unknown constants. Under this assumption, the adaptive technique is employed to estimate the bounds of unknown slipping and skidding effects of each mobile robot. To deal with the skidding effect included in kinematics, the dynamic surface design approach is applied to design a local controller for each mobile robot. Using Lyapunov stability theorem, the adaptation laws for tuning bounds of slipping and skidding are induced and it is proved that all signals of the closed-loop system are bounded and the tracking errors and the synchronization errors of the path parameters converge to an adjustable neighborhood of the origin. Finally, simulation results are provided to verify the effectiveness of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.50.5-50
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• 2002

In this paper, we propose a method using neural network (NN) to improve the motion control of a decentralized control system for cooperative transportation. In our former work, a decentralized control system for transporting a single object by multiple nonholonomic mobile robots has been developed. One of these mobile robots acts as a leader, who is assumed to be able to plan and to manipulate the omnidirectional motion of the object. Other robots, referred to as followers, cooperatively transport the object by keeping a constant position relative to the object. in this work, it is assumed that the leader can not only plan but also broadcast the local velocity of the object. Then...

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1071-1076
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• 1990

This paper proposes a navigation strategy of multiple autonomous mobile robots with communication within a specified space. Assuming that each robot has complete detectability with finite range, simple navigation strategy is derived by introducing repulsive forces between robots and attractive force between a robot and its goal point analogous to those between electric charges. When a robot is close to its goal point, a pseudo-domain based on the distance between the closest point of the domain boundary and the goal point is proposed to enhance its convergence to the goal state. This paper concludes with the results of computer simulation studies on the dynamic behavior of multiple interacting robots with the proposed navigation strategy.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.218-224
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• 2009

We propose a formation-keeping and changing methods for outdoor multiple mobile robots in chained form. Our proposed method is designed to maintain the follower to its desired distance and orientation with respect to the pole using the concept of virtual force such as potential field. The client robots use a behavior-based control to perform kinematic control to keep formation under the centralized system in our software framework. The relationship of each poles that is expressed by set of distance and angle is the description of the formation type and the type converting is performed using this set. In addition, we also examine the stability and capability in the simulation and experiments with real robots.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.12
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• pp.1321-1330
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• 2012

This paper describes an advanced formation algorithm of clustered multiple robots for their navigation using flexible formation method for collision avoidance under static environment like narrow corridors. A group of clustered multiple robots finds the lowest path cost for navigation by changing its formation. The suggested flexible method of formation transforms the basic group of mobile robots into specific form when it is confronted by particular geographic feature. In addition, the proposed method suggests to choose a leader robot of the group for the obstacle avoidance and path planning. Firstly, the group of robots forms basic shapes such as triangle, square, pentagon and etc. depending on number of robots. Secondly, the closest to the target location robot is chosen as a leader robot. The chosen leader robot uses $A^*$ for reaching the goal location. The proposed approach improves autonomous formation characteristics and performance of all system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.305-314
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• 2015

The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots' bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors' data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the "infinite repetition" or "dead cycle" situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.435-441
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• 2013

A swarm robot system consists of with multiple mobile robots, each of which is called an agent. Each agent interacts with others and cooperates for a given task and a given environment. For the swarm robotic system, the loss of the entire work capability by malfunction or damage to a single robot is relatively small and replacement and repair of the robot is less costly. So, it is suitable to perform more complex tasks. The essential component for a swarm robotic system is an inter-robot collaboration strategy for teamwork. Recently, the swarm intelligence theory is applied to robotic system domain as a new framework of collective robotic system design. In this paper, FA (Firefly Algorithm) which is based on firefly's reaction to the lights of other fireflies and their social behavior is employed to optimize the group behavior of multiple robots. The main application of the firefly algorithm is performed on path planning of swarm mobile robots and its effectiveness is verified by simulations under various conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.297-305
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• 1999

Autonomous mobile robots are required to achieve multiple goals while responding quickly to the dynamic environments. An appropriate robot control architecture, which clearly and systematically defines the relationship among the inputs, the processing functions and the outputs, thus needs to be embedded in the robot controller. This paper proposes a kind of hybrid control architecture which combines the key features of the two well-known robot control architectures; hierarchical and behavioral- based. The overall control architecture consists of three layers, i.e. the highest planner, the middle plan executor, and the lowest monitor and behavior-based controller. In the planned situation, only one behavior module is chosen by the logical coordinator in the plan executor according to the way point bin. In the exceptional situation, the central controller in the plan executor issues an additional control command to reach the planned way point. Several simulations and experiments with autonomous mobile robot show that the proposed architecture enables the robot controller to achieve the multiple sequential goals even in dynamic and uncertain environments.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.433-439
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• 2010

This paper proposes a beacon color code scheduling algorithm for the localization of multiple robots in a multi-block workspace. With the developments of intelligent robotics and ubiquitous technology, service robots are applicable for the wide area such as airports and train stations where multiple indoor GPS systems are required for the localization of the mobile robots. Indoor localization schemes using ultrasonic sensors have been widely studied due to its cheap price and high accuracy. However, ultrasonic sensors have some shortages of short transmission range and interferences with other ultrasonic signals. In order to use multiple robots in wide workspace concurrently, it is necessary to resolve the interference problem among the multiple robots in the localization process. This paper proposes an indoor localization system for concurrent multiple robots localization in a wide service area which is divided into multi-block for the reliable sensor operation. The beacon color code scheduling algorithm is developed to avoid the signal interferences and to achieve efficient localization with high accuracy and short sampling time. The performance of the proposed localization system is verified through the simulations and the real experiments.

• Journal of IKEEE
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• v.22 no.2
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• pp.440-445
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• 2018

The work presented in this paper deals with a navigation problem for a multiple mobile robots in unknown dynamic environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. In order to guide the robots along collision-free paths to reach their goal positions, a navigation method based on a combination of primary strategies has been developed. Most of these strategies are achieved by means of fuzzy logic controllers, and are uniformly applied in every robot. In order to improve the performance of the proposed fuzzy logic, the genetic algorithms were used to evolve the membership functions and rules set of the fuzzy controller. The simulation experiments verified that the proposed method effectively addresses the navigation problem.