• 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.

• Steel and Composite Structures
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• v.47 no.4
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• pp.513-521
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• 2023

The goal of this work is to create a new and improved GWO (Grey Wolf Optimizer), the so-called Robot GWO (RGWO), for dynamic and static target tracking involving multiple robots in unknown environmental conditions. From applying ourselves with the Gray Wolf Optimization Algorithm (GWO) and how it works, as the name suggests, it is a nature-inspired metaheuristic based on the behavior of wolf packs. Like other nature-inspired metaheuristics such as genetic algorithms and firefly algorithms, we explore the search space to find the optimal solution. The results also show that the improved optimal control method can provide superior power characteristics even when operating conditions and design parameters are changed.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.60-72
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• 2016

This study proposes a multi-robot system, using multiple autonomous robots, to explore concrete structures and assist in their maintenance by sealing any cracks present in the structure. The proposed system employed a new self-localization method that is essential for autonomous robots, along with a visualization system to recognize the external environment and to detect and explore cracks efficiently. Moreover, more efficient crack search in an unknown environment became possible by arranging the robots into search areas divided depending on the surrounding situations. Operations with increased efficiency were also realized by overcoming the disadvantages of the infeasible logical behavioral model design with only six basic behavioral strategies based on distributed control-one of the methods to control swarm robots. Finally, this study investigated the efficiency of the proposed multi-robot system via basic sensor testing and simulation.