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Visual object detection 기반 의수 제어
신은수(Eunsoo Shin),최태환(Taehwan Choi),나재영(Jayeong Na),유다영(Dayoung You),이회림(Hoirim Lee),임철용(Chulyong Lim),남우철(Woochul Nam) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
Most prosthetic hands cannot automatically control their gripping motions according to target objects; users need to manually select gripping motion. To address this problem, this study integrated a vision system with the prosthetic hand to autonomously detect an object to grip and conduct a suitable grip motion. The users vision was replaced with a laser pointer and mini-cam. The user needs to indicate a target object with the laser pointer. Then, the object detection model (Scaled-YOLOv4) discerns the object class and determines the gripping motion corresponding to the class. To improve the object detection accuracy, various image processing methods are applied to the detection model. Moreover, a public robot hand design (Handi-hand) was significantly modified to realize precise and robust grip motions. Actuators, joints, and stiffness components in the robot fingers were replaced with different devices for high gripping performance, and the part design was changed accordingly. The unmovable wrist was also changed to an active wrist that is controlled by a servo motor. The gripping time was determined by the user’s electromyography signals. In experiments, this prosthetic hand successfully grasped four different objects.
Visual object detection 기반 의수 제어
신은수(Eunsoo Shin),최태환(Taehwan Choi),나재영(Jayeong Na),유다영(Dayoung You),이회림(Hoirim Lee),임철용(Chulyong Lim),남우철(Woochul Nam) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
Most prosthetic hands cannot automatically control their gripping motions according to target objects; users need to manually select gripping motion. To address this problem, this study integrated a vision system with the prosthetic hand to autonomously detect an object to grip and conduct a suitable grip motion. The users vision was replaced with a laser pointer and mini-cam. The user needs to indicate a target object with the laser pointer. Then, the object detection model (Scaled-YOLOv4) discerns the object class and determines the gripping motion corresponding to the class. To improve the object detection accuracy, various image processing methods are applied to the detection model. Moreover, a public robot hand design (Handi-hand) was significantly modified to realize precise and robust grip motions. Actuators, joints, and stiffness components in the robot fingers were replaced with different devices for high gripping performance, and the part design was changed accordingly. The unmovable wrist was also changed to an active wrist that is controlled by a servo motor. The gripping time was determined by the user’s electromyography signals. In experiments, this prosthetic hand successfully grasped four different objects.
최태환(Taehwan Choi),신은수(Eunsoo Shin),유다영(Dayoung You),이회림(Hoirim Lee),나재영(Jayeong Na),이동희(Donghee Lee),임철용(Chulyong Lim),남우철(Woochal Nam) 국방로봇학회 2023 국방로봇학회 논문집 Vol.2 No.4
Most prosthetic hands cannot automatically control their gripping motions according to target objects; users need to manually select gripping motion. To address this problem, this study integrated a vision system with the prosthetic hand to autonomously detect an object to grip and conduct a suitable grip motion. The users vision was replaced with a laser pointer and mini-cam. The user needs to indicate a target object with the laser pointer. Then, the object detection model (YOLOv5) discerns the object class and determines the gripping motion corresponding to the class. To improve the object detection accuracy, various image processing methods are applied to the detection model. Moreover, a public robot hand design (Handi-hand) was significantly modified to realize precise and robust grip motions. Actuators, joints, and stiffness components in the robot fingers were replaced with different devices for high gripping performance, and the part design was changed accordingly. The unmovable wrist was also changed to an active wrist that is controlled by a servo motor. The gripping time was determined by the user’s electromyography signals. In experiments, this prosthetic hand successfully grasped four different objects.