| 研究課題/領域番号 |
14F04768
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| 研究機関 | 東京農工大学 |
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研究代表者 |
VENTURE Gentiane 東京農工大学, 工学(系)研究科(研究院), 准教授 (30538278)
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| 研究分担者 |
BONNET Vincent 東京農工大学, 工学(系)研究科(研究院), 外国人特別研究員
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| 研究期間 (年度) |
2014-04-25 – 2017-03-31
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| キーワード | 人間力学 |
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| 研究実績の概要 |
Quantification and identification of human kinematic and kinetic variables using low-cost sensors: This module will receive as input the data from low-cost FPs, IMU, similar to the one embedded in recent smart-phones and/or of a Microsoft Kinect sensor. A RGB-Depth camera tracking the IMU position will be used punctually to cancel the drift. Also, merging an IMU and a RGB-Depth camera data will allow the motion capture system to handle occlusion that can easily appears during complex industrial tasks. New adaptive filters, based on Kalman filter and Weighted Fourier linear combiner, including a constrained kinematic model of the investigated limb(s) as state vector will be developed to fuse these two sensors.
The FP will be used prior to the measurement to perform a 3D fast identification of the inertial parameters of the subject.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
The candidate is extremely brilliant and autonomous and he pursue research with a lot of enthusiasm. He also work in collaboration with students from the lab which allows to accelerate and produce excellent results.
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| 今後の研究の推進方策 |
Quantification and identification of human kinematic and kinetic variables using low-cost sensors:
This module will receive as input the data from low-cost FPs, IMU, similar to the one embedded in recent smart-phones and/or of a Microsoft Kinect sensor. A RGB-Depth camera tracking the IMU position will be used punctually to cancel the drift. Also, merging an IMU and a RGB-Depth camera data will allow the motion capture system to handle occlusion that can easily appears during complex industrial tasks. New adaptive filters, based on Kalman filter and Weighted Fourier linear combiner, including a constrained kinematic model of the investigated limb(s) as state vector will be developed to fuse these two sensors. The FP will be used prior to the measurement to perform a 3D fast identification of the inertial parameters of the subject.
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