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A Mobile Robotic Application of Naive Multi-directional Stitching with SIFT |
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Kenneth J Weber, Jaho Seo(Ontario Tech University, Canada) |
| A Mobile Robotic Application of Naive Multi-directional Stitching with SIFT
Kenneth J. Weber and Jaho Seo*
Department of Automotive and Mechatronics Engineering, Ontario Tech University,
Oshawa, L1G 0C5, Canada (kenneth.weber1@ontariotechu.net, jaho.seo@ontariotechu.ca) * Corresponding author
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Development of Wireless Pneumatic Myography Sensor for Real-time Muscle Contraction Measurement |
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Seongbin An(KAIST, Korea), Hyunjin Choi(Sangmyung University, Korea), Kyoungchul Kong(KAIST, Korea) |
| In many research areas, such as biomedical engineering, rehabilitation medicine, and sports science, electromyography (EMG) is used as a key indicator of muscle activity. While EMG provides information about active muscle activation, it does not provide information on passive activation. Muscle contraction is the result of active and passive actuation. Muscle contractions are directly related to muscle strength and provide a general understanding of muscle performance. In this paper, a real-time muscle contraction observation method using pneumatic myography (pMMG) is introduced. A modular system was developed to measure pMMG wirelessly for comparison with EMG signals. |
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A Reliability Detection Method for Position Information of a Battery-less Multi-turn Absolute Magnetic Encoder |
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JaeWan Park, Jaewook Jeon(Sungkyunkwan University, Korea) |
| This article aims to get the reliability of sensor data. The battery-less multiturn absolute (BLMA) was analyzed and considered in this study. The BLMA detects and sends the position of the shaft, and then the actuator (motor) will decide behavior. In this structure, if the encoder transmits how reliable the detected position data are, the actuator can decide whether to operate more safely depending on the situation. Finally, we design the idea to judge the reliability level of the detected position information of BLMA. This design was implemented in the BLMA, and the reliability levels were obtained. |
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Design of the Auto Gain Control Amplifier based on a Resistance Modeling of the MOSFET for a Distance Accuracy of the ToF LiDAR |
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Youngjoon Cho(GIST, Korea), Hamidreza Raei, kyihwan park(Gwangju Institute of Science and Technology, Korea) |
| For the ToF LiDAR, it is required to control the amplifying gain to ensure accurate distance measurement with wide range of intensity. In this work, the distance accuracy is investigated when TDC measures the pulse signals with different magnitudes. The electronic characteristic of MOSFET is introduced to use it as a variable resistor. Auto Gain Control method is introduced by implementing MOSFET which has a variable resistance characteristics to the op amplifier. We analayze the limitation of the available gain control range and frequency issues such as bandwidth and stability conditions in control point of view. |
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Performance Comparison between EKF and UKF in GPS/INS Low Observability Conditions |
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Kyunghyun Ryu, Jiseock Kang, Dongjun Lee(Seoul National University, Korea) |
| For the UAV localization problem, GPS-IMU-based sensor fusion is widely used. However, it is known that the GPS-IMU system becomes unobservable for a certain type of maneuver. This paper presents a comparison of two variations of Kalman filter, extended Kalman filter (EKF) and unscented Kalman filter (UKF) for unmanned aerial vehicle (UAV) localization problem in such low observability maneuver. Observability analysis and simulation are conducted on various maneuvers including constant attitude motions and orbit motion. This comparison could help the localization algorithm decision in the development of the UAV system. |
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Simultaneous and Proportional Wrist Force Intent Estimation Method using Constrained Autoencoder |
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Younggeol Cho(KAIST, Korea), Pyungkang Kim(Samsung Electronics Co., Ltd., Korea), Kyung-Soo Kim(KAIST, Korea) |
| In this study, we propose an intention estimation model for prosthetic hand control based on bio-signals. The proposed model enables simultaneous and proportional control of fingers and has a robust feature of electrode position.
Methods: We propose a model for real-time estimation of muscle activation based on neurophysiology and a high-performance finger force estimation model that is robust to the electrode position using the estimated muscle unit activation. The experiment was performed on 10 Able-body, and the performance of the proposed model was compared with four regression models through offline/online tests. |
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