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Simultaneous and Proportional Wrist Force Intent Estimation Method using Constrained Autoencoder
Younggeol Cho,Pyungkang Kim,Kyung-Soo Kim 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
The proposed model is capable of estimating multiple degrees of freedom wrist force simultaneously and proportionally. In the case of previous studies, it has been developed from a method of performing only a set motion based on pattern recognition, and studies that proportionally estimate wrist and finger strength are in progress. In this context, the wrist force was estimated using a method that modified the structure of the autoencoder, which is one of the artificial neural networks with high intention estimation performance compared to previous studies. This study was conducted with 2 degrees of freedom (Wrist flexion, Wrist extension, Ulnar deviation, Radial deviation) of the wrist. The proposed model showed high model accuracy and independence between degrees of freedom compared to similar previous models. Also, as a result of an online simulation test that reflects the real-time prosthetic control situation, 5 out of 6 performance indicators showed higher performance than the comparative model. As a result of this study, it was possible to infer that the accuracy of the model and the securing of independence between the degrees of freedom have a great effect on the control of the actual prosthetic arm including humans.
Younggeol. Cho,Minsu. Cho,Yeungseok. Lee,Kyung-Soo Kim 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
The aim of this study is to design a wearable sensor device and to optimize the position of the sensor attachment, which is one of the important factors for the prosthetic hand control based on the surface electromyography (sEMG). Through anatomical examination of the arm, the independence of the surface electromyogram acquired in each channel is increased and the signal to noise ratio (SNR) is also increased by signal processing. We introduce a study on the research trend and sensor position of the surface EMG-based prosthetic hand in Introduction. In body, the design and characteristics of the developed sensor are explained, and correlation analysis between each channel and finger force is performed by selecting the position of the sensor through anatomical examination of the arm. In conclusion, we use the correlation analysis result and find the optimal sensor location.
Training Strategy and sEMG Sensor Positioning for Finger Force Estimation at Various Elbow Angles
Minsu Cho,Younggeol Cho,Kyung-Soo Kim 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.5
Recently, several simultaneous proportional control techniques using surface electromyography (sEMG) have been developed to control protheses. However, there is a gap between research and clinical applications. This gap is due to estimation error in interposition and sEMG sensor parameters. Many previous studies have shown that the estimation accuracy of the model decreases at the interposition. Several studies have also found that the number and placement of sEMG sensors affect the performance of the models. In this paper, we propose a training strategy and guidelines for positioning sEMG sensors to reduce this gap. In this study, the finger force estimation model was trained by combining training data from various elbow angles into one feature vector. This training protocol reduced the root mean square error (RMSE) by 12.40% and increased the interdependency ratio (IR) by 3.40% in interposition. We also used the correlation coefficient between the finger force and sEMG signal as an evaluation index to determine the optimal placement of the sEMG sensor. The models trained using the channels with high correlation coefficients achieved better estimation performance, and the number of channels was reduced to four. When the model was retrained with the proposed training protocol using these 4 channels, the RMSE decreased by 10.73% and the IR increased by 1.87% in interposition. We expect the training strategy to close the researchapplication gap by reducing the number of sensors, finding the optimal placement of the sensors, and reducing the estimated error in interposition.
조영걸(Younggeol Cho),이준희(Junhee Lee) 한국정보기술학회 2021 Proceedings of KIIT Conference Vol.2021 No.11
전장 환경에서 감시정찰은 임무 성공을 위해 중요하다. 최근 국방 분야에서는 딥러닝 기반의 물체 인식 기술을 도입하고 있으나, 대부분의 물체 인식 모델은 소형 물체 인식에 어려움을 겪기 때문에 먼 거리의 물체를 감시하는 것이 중요한 감시정찰에 치명적이다. 본 논문에서는 물체 인식 모델의 수정 없이 소형 물체를 인식할 수 있도록 모델 입력 크기보다 큰 해상도의 이미지를 분할하여 입력하고 그 결과를 병합하는 기법을 제안하고 소형 물체 인식 정확도가 향상되었음을 확인하였다. Surveillance and reconnaissance are important for mission success in a battle. Recently, deep learning-based object detection has been introduced in the defense field. But most object detectors have difficulties in detecting small objects, which is critical to surveillance and reconnaissance that require monitoring objects over long distances. This paper suggests a technique to split an input image with larger resolution than the input size of a detector into smaller images, input them to the detector, and merge the results to detect small objects without modifying the model. The proposed method increased the accuracy of small object detection.
Development of Stiffness Analysis Program for Automotive Wheel Bearing
Inha Lee(이인하),Younggeol Cho(조영걸),Jungho An(안정호),Youngmin Cho(조영민),Munsung Kim(김문성),Cheonsoo Jang(장천수),Younghwan Lee(이영환),Seungpyo Lee(이승표) 한국자동차공학회 2012 한국자동차공학회 부문종합 학술대회 Vol.2012 No.5
Automotive wheel bearing is an essential component of the vehicle and transmits engine power into wheels and supports vehicle weight. As comfortable ride has recently been the common interest, the stiffness of bearing which affects the steering performance becomes significant. In this study, the program BSAP was developed to carry out the stiffness analysis by designer easily and quickly. BSAP has three templates; CATIA template, AFC template, and Report template. In CATIA template, 3D analysis model was generated from the CAD model by eliminating useless fillets and holes and assigning heat treatment parts. Material property, boundary conditions and loadings were applied and analysis was performed in AFC template. Finally, analysis results were reported automatically in Report template. Bearing stiffness analysis was performed by using the BSAP. To verify the reliability of BSAP, the analysis results were compared with experiment results. They showed good agreement with the experiment results.
김봉철(Bongchul Kim),조영걸(Younggeol Cho),이왕열(Wangyeol Lee),이승표(Seungpyo Lee) 한국자동차공학회 2010 한국자동차공학회 학술대회 및 전시회 Vol.2010 No.11
Automotive wheel bearing is one of important parts that transmits engine power into wheels and supports vehicle weight. In this study, strength analysis and design optimization are carried out for wheel bearing. First, for cracked bearing strength analysis is performed to calculate the stress distribution. Next, optimization is performed in order to minimize the stress of cracked region. From the result, we assumed that the crack cannot be occurred.