• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.55-63
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• 2007

Mobile robots traveling on rough terrain need several algorithms to overcome obstacles. In this paper, we propose the step-type obstacle traversal algorithm to adapt the mobile robot with six arms and wheels to travel on rough terrain. Obstacle traversal is composed of two different stages: planning and control. In planning stage, the required joint torque of each arm as well as the interference between the wheels and the arms are analyzed to guarantee traversing obstacles. Control stage includes such steps as checking distance to obstacle, determining the height and length of obstacle, performing arm motion according to sensed torque data, and evaluating safety at every instance. The proposed algorithm is designed and implemented for CALEB 1 six legged robot developed in the laboratory and verified by simulation and experiment in outdoor environment.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.221-228
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• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

• Physical Therapy Rehabilitation Science
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• v.8 no.2
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• pp.93-98
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• 2019

Objective: The purpose of this study was to investigate the effect of robot arm reach training on upper extremity functional movement in chronic stroke survivors. Design: One group pretest-posttest design. Methods: Thirteen chronic stroke survivors participated in this study. Robot arm reach training was performed with a Whole Arm Manipulator (WAM) and a 120-inch projective display to provide visual and auditory feedback. During the robotic arm reach training, WAM provided gravity compensation and assist-as-needed (AAN) force according to the robot control mode. When a participant could not move the arm toward the target for more than 2 seconds, WAM provided AAN force to reach the desired targets. All patients participated in the training for 40 minutes per day, 3 times a week, for 4 weeks. Main outcome measures were the Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT) and Box and Block Test (BBT) to assess upper extremity functional movement. Results: After 4 weeks, significant improvement was observed in upper extremity functional movement (FMA: 42.15 to 46.23, BBT: 12.23 to 14.00, p<0.05). In the subscore analysis of the FMA upper extremity motor function domains, significant improvement was observed in upper extremity and coordination/speed units (p<0.05). However, there were no significant differences in the ARAT. Conclusions: This study showed the positive effects of robot arm reach training on upper extremity functional movement in chronic stroke survivors. In particular, we confirmed that robot arm reach training could have a positive influence by leading to improvement of motor recovery of the proximal upper extremity.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.27-33
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• 2011

Control and trajectory generation of a 7 DOF anthropomorphic robot arm suffer from computational complexity and singularity problem because of numerical inverse kinematics. To deal with such problems, analytical methods for a redundant robot arm have been researched to enhance the performance of inverse kinematics. In this research, we propose an analytical inverse kinematics algorithm for a 7 DOF anthropomorphic robot arm. Using this algorithm, it is possible to generate a trajectory passing through the singular points and intuitively move the elbow without regard to the end-effector pose. Performance of the proposed algorithm was verified by various simulations. It is shown that the trajectory planning using this algorithm provides correct results near the singular points and can utilize redundancy intuitively.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.168-171
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• 1993

In this paper, we design a time optimal controller of a dual arm robot to handle the object. Differently from the master-slave type robot, same priority is imposed on the both of the arms for effective handling the specifed object. For finding a time optimal collision-free trajectory, a graphical method is applied for the robot with two degree of freedom. Some simulation results show the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1220-1230
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• 2006

In this paper, we propose a flew technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.101-102
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• 2011

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.306-312
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• 2017

Recently, development of robot technology has been actively investigated that industrial robots are used in various other fields. However, the interface of the industrial robot is limited to the planned and manipulated path according to the target point and reaching time of the robot arm. Thus, it is not easy to create or change the various paths of the robot arm in other applications, and it is not easy to control the robot so that the robot arm passes the specific point precisely at the desired time during the course of the path. In order to overcome these limitations, this paper proposes a new-media content management platform that can manipulate 6 DOF industrial robot arm using 3D game engine. In this platform, the user can directly generate the motion of the robot arm in the UI based on the 3D game engine, and can drive the robot in real time with the generated motion. The proposed platform was verified using 3D game engine Unity3D and KUKA KR-120 robot.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.437-440
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• 1988

This paper discuss which new dynamic control method for robot arm. It is basedon nonlinear feedback and T transformation which externally linearizes the whole system and provides simultaneous output decoupling. The nonlinear feedback augmented with optimal error correcting controller, which operates on the task error level. Computer simulation were appled to evaluate the performance of new dynamic control method. The simulation results are discussed in detail.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.9
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• pp.14-22
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• 2009