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Model-Based Real-Time Motion Tracking Using Dynamical Inverse Kinematics

1
Dynamic Interaction Control, Center for Robotics and Intelligent Systems, Istituto Italiano di Tecnologia, 16163 Genoa, Italy
2
Machine Learning and Optimisation, The University of Manchester, Manchester M13 9PL, UK
*
Author to whom correspondence should be addressed.
Algorithms 2020, 13(10), 266; https://doi.org/10.3390/a13100266
Received: 10 September 2020 / Revised: 14 October 2020 / Accepted: 17 October 2020 / Published: 20 October 2020
(This article belongs to the Section Algorithms for Multidisciplinary Applications)
This paper contributes towards the development of motion tracking algorithms for time-critical applications, proposing an infrastructure for dynamically solving the inverse kinematics of highly articulate systems such as humans. The method presented is model-based, it makes use of velocity correction and differential kinematics integration in order to compute the system configuration. The convergence of the model towards the measurements is proved using Lyapunov analysis. An experimental scenario, where the motion of a human subject is tracked in static and dynamic configurations, is used to validate the inverse kinematics method performance on human and humanoid models. Moreover, the method is tested on a human-humanoid retargeting scenario, verifying the usability of the computed solution in real-time robotics applications. Our approach is evaluated both in terms of accuracy and computational load, and compared to iterative optimization algorithms. View Full-Text
Keywords: motion tracking; kinematic estimation; inverse kinematics; motion retargeting motion tracking; kinematic estimation; inverse kinematics; motion retargeting
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MDPI and ACS Style

Rapetti, L.; Tirupachuri, Y.; Darvish, K.; Dafarra, S.; Nava, G.; Latella, C.; Pucci, D. Model-Based Real-Time Motion Tracking Using Dynamical Inverse Kinematics. Algorithms 2020, 13, 266. https://doi.org/10.3390/a13100266

AMA Style

Rapetti L, Tirupachuri Y, Darvish K, Dafarra S, Nava G, Latella C, Pucci D. Model-Based Real-Time Motion Tracking Using Dynamical Inverse Kinematics. Algorithms. 2020; 13(10):266. https://doi.org/10.3390/a13100266

Chicago/Turabian Style

Rapetti, Lorenzo, Yeshasvi Tirupachuri, Kourosh Darvish, Stefano Dafarra, Gabriele Nava, Claudia Latella, and Daniele Pucci. 2020. "Model-Based Real-Time Motion Tracking Using Dynamical Inverse Kinematics" Algorithms 13, no. 10: 266. https://doi.org/10.3390/a13100266

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