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의인화형 로봇 손을 장착한 협동로봇의 ROS 기반 통합제어시스템 개발
박현준(Hyeonjun Park),김동한(Donghan Kim) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.8
In this paper, we introduce an integrated control system for cooperative robot with anthropomorphic robot hand based on ROS (Robot Operating System). In order to increase reusability and scalability, the integrated control system consists of ROS nodes. Based on this system, we built the pick & place experimental environment considering the region of motion of UR3 in the Gazebo simulator and applied it in the real world.
최소침습술을 위한 의료용 인스트루먼트의 동작 성능 향상
박현준(Hyeonjun Park),원종석(Jongseok Won),박재흥(Jaeheung Park) 제어로봇시스템학회 2013 제어·로봇·시스템학회 논문지 Vol.19 No.12
This paper presents feedforward controllers to improve the control performance of the motion and grasping force of a surgical instrument used in an MIS (Minimally Invasive Surgery) robot. The surgical instrument has a long distance between the drive motors and its active joints. Therefore, the gripper on the instrument is controlled by a cable drive mechanism, which generates a coupled motion between the wrist joint and the grip direction. In order to solve the problem, this paper analyzes the pulley composition of the surgical instrument and proposes feedforward controllers to eliminate the coupled motion. Furthermore, feedforward controllers to regulate the grasping force are proposed to deal with another coupling problem between the grasping force of the instrument and the motion of the instrument joints. The experimental results demonstrate the improved control performance of the motion and grasping force of the instrument.
Transformer based Collision Detection Approach by Torque Estimation using Joint Information
Jiwon Park(박지원),Daegyu Lim(임대규),Sumin Park(박수민),Hyeonjun Park(박현준) 한국로봇학회(논문지) 2024 로봇학회 논문지 Vol.19 No.3
With the rising interaction between robots and humans, detecting collisions has become increasingly vital for ensuring safety. In this paper, we propose a novel approach for detecting collisions without using force torque sensors or tactile sensors, utilizing a Transformer-based neural network architecture. The proposed collision detection approach comprises a torque estimator network that predicts the joint torque in a free-motion state using Synchronous time-step encoding, and a collision discriminator network that predicts collisions by leveraging the difference between estimated and actual torques. The collision discriminator finally creates a binary tensor that predicts collisions frame by frame. In simulations, the proposed network exhibited enhanced collision detection performance relative to the other kinds of networks both in terms of prediction speed and accuracy. This underscores the benefits of using Transformer networks for collision detection tasks, where rapid decision-making is essential.
2단계 히든마코프 모델을 이용한 제스쳐의 성능향상 연구
정훤재(Hwon-Jae Jung),박현준(Hyeonjun Park),김동한(Donghan Kim) 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.21 No.11
In recent years in the field of robotics, various methods have been developed to create an intimate relationship between people and robots. These methods include speech, vision, and biometrics recognition as well as gesture-based interaction. These recognition technologies are used in various wearable devices, smartphones and other electric devices for convenience. Among these technologies, gesture recognition is the most commonly used and appropriate technology for wearable devices. Gesture recognition can be classified as contact or noncontact gesture recognition. This paper proposes contact gesture recognition with IMU and EMG sensors by using the hidden Markov model (HMM) twice. Several simple behaviors make main gestures through the one-stage HMM. It is equal to the Hidden Markov model process, which is well known for pattern recognition. Additionally, the sequence of the main gestures, which comes from the one-stage HMM, creates some higher-order gestures through the two-stage HMM. In this way, more natural and intelligent gestures can be implemented through simple gestures. This advanced process can play a larger role in gesture recognition-based UX for many wearable and smart devices.
개인용 탑승 로봇의 안정성 평가를 위한 사람 허리 움직임을 묘사하는 동적 더미 시스템의 개발
권태양(Taeyang Gwon),박현준(Hyeonjun Park),이상흠(Sanghuem Lee),김동한(Donghan Kim) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.8
In this paper, we propose a dynamic dummy system that describes the movement of a person"s waist movement. Person carrier robots have a significant impact on the movement of human beings. While the market for person carrier robot grows, the need to assess their stability is becoming more important. Therefore, in order to accurately evaluate stability, it is essential to imitate human movements.
인공신경망을 이용한 모바일 매니퓰레이터 통합제어 알고리즘에 관한 연구
이상흠(Sangheum Lee),박현준(Hyeonjun Park),김동한(Donghan Kim) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.8
Redundancy makes it difficult to control mobile manipulator. When it performs a simple mission, there is no control problem. However, if it faces a crowded environment, it might have control problems. In this study, integrated control algorithms were studied as a method of artificial neural network(ANN) training based on mobile manipulator kinematics data. As the goal position of the end effector of the manipulator is determined, the mobile base is moved to the position where the kinematic solution exists. In that way, the robotic system can be controlled by a single control input.
김기현(Peter Ki Kim),박현준(Hyeonjun Park),배지훈(Ji-Hun Bae),박재한(Jae-Han Park),이동혁(Dong-Hyuk Lee),박재흥(Jaeheung Park),경진호(Jin-Ho Kyung),백문홍(Moon-Hong Baeg) 제어로봇시스템학회 2016 제어·로봇·시스템학회 논문지 Vol.22 No.8
While anthropomorphic robots are gaining interest, dual-arm robots are widely used in the industrial environment. Many methods exist in order to implement bimanual tasks by dual-arm robot. However, kinesthetic teaching is used in this paper. This paper suggests three different kinesthetic teaching methods that can implement most of the human task by the robot. The three kinesthetic teaching methods are joint level, task level, and contact level teaching. The task introduced in this paper is box packing, which is a popular and complex task in industrial environment. The task is programmed into the dual-arm robot by utilizing the suggested kinesthetic teaching method, and this paper claims that most tasks can be implemented by using the suggesting kinesthetic teaching methods.