• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.152-152
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• 2000

In this paper, we propose a new approach to intelligent motion and autonomous maneuvering of mobile robots using hybrid system. In high Level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot as a low vevel are specified in the abstracted motions, The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.164-169
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• 1998

Complex "lifelike" behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, "flocking" and "arrangement", of multiple autonomous mobile robots are represented by a small number of fuzzy rules. Fuzzy rules in Sugeno type and their related paramenters are automatically generated from clustering input-output data obtained from the algorithms the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.69-74
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• 2009

In this paper, we propose a method of ontology-based control of autonomous robots. Advancing one step further from using ontology as a hierarchical storage of information, the proposed method shows how to control robots through ontology inference. That is, the information on obstacles detected by robots is represented as an ontology, and robots' action planning and control are performed according to robots' surroundings through ontology inference. We make a differentially driven robot and illustrate the effectiveness of the proposed method via the experiment of the robot's navigation in real environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.79-82
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• 1997

In this paper, group intelligence "arrangement" bahavior of autonomous mobile robots(AMRs) is realized by the fuzzy rules. The fuzzy rules for the arrangement are generated from clustering the input-output data. Simulation shows that a small-number of fuzzy rules successfully realizes the arrangement behavior of AMRs.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.185-190
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• 2002

In distributed autonomous robotic systems (DARS), each robot must behave by itself according to its states ad environments, and if necessary, must cooperate with other robots in order to carry out their given tasks. Its most significant merit is that they determine their behavior independently, and cooperate with other robots in order to perform the given tasks. Especially, in DARS, it is essential for each robot to have evolution ability in order to increase the performance of system. In this paper, a schema co-evolutionary algorithm is proposed for the evolution of collective autonomous mobile robots. Each robot exchanges the information, chromosome used in this algorithm, through communication with other robots. Each robot diffuses its chromosome to two or more robots, receives other robot's chromosome and creates new species. Therefore if one robot receives another robot's chromosome, the robot creates new chromosome. We verify the effectiveness of the proposed algorithm by applying it to cooperative search problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.165-167
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• 2011

Autonomous robots are intelligent machines that are capable of performing task in the world themselves with little or no human intervention. One of the main reason autonomous robots gained popularity in human's world is their ability to perform task with high degree of precision, accuracy and also consistency. One of the most studied fields in autonomous robot is the ability of decision making in robots. To tackle the ability of robots to make decision, this paper proposed an Autonomous Maze Solving Robot that is able to solve a maze using the optimum solution. The maze and the design of the robot are in compliance with IEEE Micromouse competition rules and regulation. Micromouse is an autonomous maze solving robot that shall be able to explore a maze on its own from a predefined starting location and find the optimum path to reach the predefined goal in the maze without human's intervention.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.328-332
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• 2023

The Army has presented eight game-changers for future warfare through 'Army Vision 2050,' including Intelligent Combat Robots, Super Soldiers, Energy Weapons, Hypersonic Weapons, Non-lethal Weapons, Autonomous Mobile Equipment, Intelligent Command and Control Systems, and Energy Supply Systems. This study focuses on Intelligent Combat Robots, considering them as the most crucial element among the mentioned innovations. How will Intelligent Combat Robots be utilized on the future battlefield? The future battlefield is expected to take the form of combined human-robot warfare, where advancements in science and technology allow intelligent robots to replace certain human roles. Especially, tasks known as Dirty, Difficult, Dangerous, and Dull (4D) in warfare are expected to be assigned to robots. This study suggests three forms of Intelligent Robots: humanoid robots, biomimetic robots, and swarm drones.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.229-235
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• 2003

We designed a family of completely autonomous mobile robots with local intelligence. Each robot has a number of on-board sensors, including vision, and does not rely on global positioning systems The on-board embedded controller is sufficient to analyze several low-resolution color images per second. This enables our robots to perform several complex tasks such as navigation, map generation, or providing intelligent group behavior. Not being limited to playing the game of soccer and being completely autonomous, we are also looking at a number of other interesting scenarios. The robots can communicate with each other, e.g. for exchanging positions, information about objects or just the local states they are currently in (e.g. sharing their current objectives with other robots in the group). We are particularly interested in the differences between a behavior-based approach versus a traditional control algorithm at this still very low level of action.