• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.364-371
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• 2014

The purpose of this paper is to review recent developments in lower limb exoskeletons. The exoskeleton system is a human-robot cooperation system that enhances the performance of the wearer in various environments while the human operator is in charge of the position control, contextual perception, and motion signal generation through the robot's artificial intelligence. This system is in the form of a mechanical structure that is combined to the exterior of a human body to improve the muscular power of the wearer. This paper is followed by an overview of the development history of exoskeleton systems and their three main applications in military/industrial field, medical/rehabilitation field and social welfare field. Besides the key technologies in exoskeleton systems, the research is presented from several viewpoints of the exoskeleton mechanism, human-robot interface and human-robot cooperation control.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.3 s.258
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• pp.285-294
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• 2007

Previously, ASCI(Automation System for Curtain-wall Installation) which combined with a multi-DOF manipulator to a mini-excavator was developed and applied on construction site. As result, the operation by one operator and more intuitive operation method are proposed to improve ASCI's operation method which need one person with a remote joystick and another operating an excavator. The human-robot cooperative system can cope with various and untypical constructing environment through the real-time interacting with a human, robot and constructing environment simultaneously. The physical power of a robot system helps a human to handle heavy construction materials with relatively scaled-down load. Also, a human can feel and response the force reflected from robot end effecter acting with working environment. This paper presents the feasibility study regarding the application of the proposed human-robot cooperation control for construction robot through experiments on a 2DOF manipulator.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.236-242
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• 2003

This paper presents a cooperation strategy between a human operator and autonomous robots for an interactive robot soccer game, The interactive robot soccer game has been developed to allow humans to join into the game dynamically and reinforce entertainment characteristics. In order to make these games more interesting, a cooperation strategy between humans and autonomous robots on a team is very important. Strategies can be pre-programmed or learned by robots themselves with learning or evolving algorithms. Since the robot soccer system is hard to model and its environment changes dynamically, it is very difficult to pre-program cooperation strategies between robot agents. Q-learning - one of the most representative reinforcement learning methods - is shown to be effective for solving problems dynamically without explicit knowledge of the system. Therefore, in our research, a Q-learning based learning method has been utilized. Prior to utilizing Q-teaming, state variables describing the game situation and actions' sets of robots have been defined. After the learning process, the human operator could play the game more easily. To evaluate the usefulness of the proposed strategy, some simulations and games have been carried out.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.404-412
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• 2020

Typically everyday human life tasks involve at least two people moving objects such as tables and beds, and the balancing of such object changes based on one person's action. However, many studies in previous work performed their tasks solely on robots without factoring human cooperation. Therefore, in this paper, we propose cooperative robot for table balancing using Q-learning that enables cooperative work between human and robot. The human's action is recognized in order to balance the table by the proposed robot whose camera takes the image of the table's state, and it performs the table-balancing action according to the recognized human action without high performance equipment. The classification of human action uses a deep learning technology, specifically AlexNet, and has an accuracy of 96.9% over 10-fold cross-validation. The experiment of Q-learning was carried out over 2,000 episodes with 200 trials. The overall results of the proposed Q-learning show that the Q function stably converged at this number of episodes. This stable convergence determined Q-learning policies for the robot actions. Video of the robotic cooperation with human over the table balancing task using the proposed Q-Learning can be found at http://ibot.knu.ac.kr/videocooperation.html.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.183-184
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.25.3-25
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• 2001

This paper describes a control method of a robot cooperating with a human. A task in which a robot and a human move an object cooperatively is considered. To develop the force controller of the robot, the characteristics of human arm are investigated. The arm is forced to move along a trajectory in the experiment and the exerted force and the displacement are analyzed, It is found the force characteristics of the human arm is regarded as an optimal damper with minimizing a cost function. Then, the model is implemented to a robot and the cooperation of the robot and a human operator is examined. The effectiveness of the derived model is investigated and the experimental results show that the human moves the object supported by the robot with a minimum jerk trajectory.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.59.2-59
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• 2001

This paper presents an evolvable cooperation strategy based on a genetic programming for the interactive robot soccer game. The interactive robot soccer game has been developed to allow a person to join in the game dynamically and to reinforce entertainment characteristics. In this game, a cooperation strategy between humans and autonomous robots is very important in order to make the game more enjoyable. First of all, necessary action sets for the cooperation strategy and its strategy structure are presented. In the first stage, a blocking action that an autonomous robot cut off an enemy robot from disturbing the way of the human controlled robot has been considered. The success probability of the blocking action has beer obtained in ...

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8563-8567
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• 2015

We propose a human-robot interaction(HRI) platform based on motion capture and mapping. Platform consists of capture, processing/mapping, and action parts. A motion capture sensor, computer, and avatar and/or physical robots are selected as capture, processing/mapping, and action part(s), respectively. Case studies-an interactive presentation and LEGO robot car are presented to show the design and implementation process of Kinect based HRI platform.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7508-7512
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• 2015

We propose a brain-machine interface(BMI) based human-robot interaction(HRI) platform which operates machines by interfacing intentions by capturing brain waves. Platform consists of capture, processing/mapping, and action parts. A noninvasive brain wave sensor, PC, and robot-avatar/LED/motor are selected as capture, processing/mapping, and action part(s), respectively. Various investigations to ensure the relations between intentions and brainwave sensing have been explored. Case studies-an interactive game, on-off controls of LED(s), and motor control(s) are presented to show the design and implementation process of new BMI based HRI platform.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.173-174
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• 2010