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The aim of this work is to provide a humanoid robot that is able to replicate human's upper body movements by using motion capture data acquired from Biomotion+, developed by the Hamlyn Centre. This work proposes an upper limb motion imitation module for a humanoid robot. The module calculates joint angle trajectories, based on motion capture data, and sends these trajectories to a humanoid robot...
Traditional vision-based and commercial motion-capture systems acquire human body motion within studio. We present an ubiquitous human limb motion capture system using wearable micro-inertial-sensors accelerometers and gyroscopes. The sensor units are attached to segments of upper limb, and the collected acceleration and angular rate data are transmitted to the PC via USB interface. Motion data are...
We have presented our work in progress on human body motion capture using wearable mirco-inertial sensors only. Novel drift model are proposed to deal with inherent bias problem of inertial sensors, and Extended Dynamic Bayesian Network (EDBN) are employed to model the constraints among human body segments. Given the uncertainties of human movements, multiple models are proposed to describe the behaviors...
Motion capture serves as a key technology in a wide spectrum of applications, including interactive game and learning, animation, film special effects, health-care and navigation. The existing human motion capture techniques, which use structured multiple high resolution cameras in the dedicated studio, are complicated and expensive. As rapid development of micro inertial sensors-on-chip, ubiquitous,...
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