• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.260-269
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• 2021

To verify performance or conduct experiments using actual robots, a lot of costs are needed such as robot hardware, experimental space, and time. Therefore, a simulation environment is an essential tool in robotics research. In this paper, we develop the HUMIC simulator using ROS and Gazebo. HUMIC is a humanoid robot, which is developed by HCIR Lab., for human-robot interaction and an upper body of HUMIC is similar to humans with a head, body, waist, arms, and hands. The Gazebo is an open-source three-dimensional robot simulator that provides the ability to simulate robots accurately and efficiently along with simulated indoor and outdoor environments. We develop a GUI for users to easily simulate and manipulate the HUMIC simulator. Moreover, we open the developed HUMIC simulator and GUI for other robotics researchers to use. We test the developed HUMIC simulator for object detection and reinforcement learning-based navigation tasks successfully. As a further study, we plan to develop robot behavior intelligence based on reinforcement learning algorithms using the developed simulator, and then apply it to the real robot.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.507-515
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• 2019

The positive effects of 'robot actor' born in the age of artificial intelligence on the characteristics of theater (comprehensive, liveness, duality, planning) is due to the collaboration with 'robot' engineers, which increases the comprehensive. It is possible to respond to it, so that various reaction are maintained in every performance, and enhanced illusion can be provided in 'robot' material works in which 'robot actor' plays the role of 'robot'. However, the power focused on the director can reduce the comprehensiceness, the synthesis is reduced, and the 'robot actor' cannot perform the sweat or breath of 'human actor'. In itself, duality is incomplete. In addition, there is a high risk that the improvisation within the scope of planning is likely to occur as a sudden reaction, which may limit the postponement of the 'human actor'. Based on these findings, 'philosophy', 'science' and 'art' can predict the development of artificial intelligence side by side. It is considered necessary to study to redefine the direction and identity of arts and theater that should be moved forward.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.385-391
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• 2008

Robotics has emerged as an important field for the future. It is our vision that robots in future will be able to transcend these precincts and work side by side humans for the greater good of mankind. We developed a face robot for this purpose. However, Life like robots demands a certain level of intelligence. Some scientists have proposed an event based learning approach, in which the robot can be taken as a small child and through learning from surrounding entities develops its own personality. In fact some scientists have proposed an entire new personality of the robot itself in which robot can have its own internal states, intentions, beliefs, desires and feelings. Our approach should not only be to develop a robot personality model but also to understand human behavior and incorporate it into the robot model. Human's personality is very complex and rests on many factors like its physical surrounding, its social surrounding, and internal states and beliefs etc. This paper discusses the development of this platform to evaluate this and develop a standard by a society based approach including the cultural paradigm. For this purpose the fuzzy control theory is used. Since the fuzzy theory is very near human analytical thinking it provides a very good platform to develop such a model.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1190-1195
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• 2003

In this paper, it is shown how a robot with n passive trailers can be controlled in backward direction. When driving backward direction, a kinematic model of the system is represented highly nonlinear equations. The problem is formulated as a trajectory following problem, rather than control of independent generalized coordinates. Also, the state and input saturation problems are formulated as a trajectory generation problem. The trajectory is traced by a rear hinge point of the last trailer, and reference trajectories include line segments, circular shapes and rectangular turns. Experimental verifications were carried out with the PSR-2(public service robot $2^{nd}$ version) with three passive trailers. Experimental result showed that the backward motion control can be successfully carried out using the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.921-927
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• 2013

This paper presents a user interface for vision based indirect teaching of a robotic manipulator with Kinect and IMU (Inertial Measurement Unit) sensors. The user interface system is designed to control the manipulator more easily in joint space, Cartesian space and tool frame. We use the skeleton data of the user from Kinect and Wrist-mounted IMU sensors to calculate the user's joint angles and wrist movement for robot control. The interface system proposed in this paper allows the user to teach the manipulator without a pre-programming process. This will improve the teaching time of the robot and eventually enable increased productivity. Simulation and experimental results are presented to verify the performance of the robot control and interface system.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.12-21
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• 2021

This article presents the future vision and core technologies of the "Life Companion Robot," which is one of the 12 future concepts introduced in the ETRI Technology Roadmap published in November 2020. Assistant robots, care robots, and life support robots were proposed as the development stages of life companion robots. Further, core technologies for each of the ten major roles that must be directly or indirectly performed by life companion robots are introduced. Finally, this article describes in detail three major artificial intelligence technologies for autonomous robots.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.165-170
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• 2023

This study focuses on the development of intelligent combat robot systems for future warfare. The research is structured as follows: First, the introduction presents the rationale for researching intelligent combat robots and their potential to become game changers in future warfare. Second, in the context of the intelligent robot paradigm, this study proposes the need for military organizations to innovate their combat concepts and weapon systems through the effective utilization of Artificial Intelligence, Cognitive, Biometric, and Mechanical technologies. This forms the theoretical background of the study. Third, the analysis of intelligent robot systems considers five examples: humanoid robots, jumping robots, wheeled and quadrupedal pack robots, and tank robots. Finally, the discussion and conclusion propose that intelligent combat robots should be selected as game changers in military organizations for future warfare, and suggest further research in this area.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.369-376
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• 2021

With the development of artificial intelligence (AI) technology, discussions on the use of artificial intelligence are actively taking place in many fields, and various policies for nurturing artificial intelligence talents are being promoted in the field of education. In this study, we propose a robot programming framework using artificial intelligence technology, and based on this, we use Python, which is used frequently in the machine learning field, and an educational robot that is highly utilized in the field of education to provide artificial intelligence. (AI) education program was proposed. The level of autonomous driving (levels 0-5) suggested by the International Society of Automotive Engineers (SAE) is simplified to four levels, and based on this, the camera attached to the robot recognizes and detects lines (objects). The goal was to make a line detector that can move by itself. The developed program is not a standardized form of solving a given problem by simply using a specific programming language, but has the experience of defining complex and unstructured problems in life autonomously and solving them based on artificial intelligence (AI) technology. It is meaningful.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.457-467
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• 2004

In this paper, a robot is considered as an agent, a structure of robot is presented which consisted by multi-subagents and they have diverse capacity such as perception, intelligence, action etc., required for robot. Also, subagents are consisted by micro-agent($\mu$agent) charged for elementary action required. The structure of robot control have two sub-agents, the one is behavior based reactive controller and action selection sub agent, and action selection sub-agent select a action based on the high label action and high performance, and which have a learning mechanism based on the reinforcement learning. For presented robot structure, it is easy to give intelligence to each element of action and a new approach of multi robot control. Presented robot is simulated for two goals: chaotic exploration and obstacle avoidance, and fabricated by using 8bit microcontroller, and experimented.

• Journal of the Korea Safety Management & Science
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• v.25 no.3
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• pp.17-22
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• 2023

As the importance of artificial intelligence grows rapidly and emerges as a leader in technology, it is becoming an important variable in the next-generation industrial system along with the robot industry. In this study, a safety system was developed using deep learning technology to provide worker safety in a robot workplace environment. The implemented safety system has multiple cameras installed with various viewing directions to avoid blind spots caused by interference. Workers in various scenario situations were detected, and appropriate robot response scenarios were implemented according to the worker's risk level through IO communication. For human detection, the YOLO algorithm, which is widely used in object detection, was used, and a separate robot class was added and learned to compensate for the problem of misrecognizing the robot as a human. The performance of the implemented system was evaluated by operator detection performance by applying various operator scenarios, and it was confirmed that the safety system operated stably.