Biomechanical Trajectory Optimization of Human Sit-to-Stand Motion With Stochastic Motion Planning Framework
Issued Date
2022-11-01
Resource Type
eISSN
25763202
Scopus ID
2-s2.0-85137938668
Journal Title
IEEE Transactions on Medical Robotics and Bionics
Volume
4
Issue
4
Start Page
1022
End Page
1033
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE Transactions on Medical Robotics and Bionics Vol.4 No.4 (2022) , 1022-1033
Suggested Citation
Sharma B., Pillai B.M., Suthakorn J. Biomechanical Trajectory Optimization of Human Sit-to-Stand Motion With Stochastic Motion Planning Framework. IEEE Transactions on Medical Robotics and Bionics Vol.4 No.4 (2022) , 1022-1033. 1033. doi:10.1109/TMRB.2022.3205509 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/84245
Title
Biomechanical Trajectory Optimization of Human Sit-to-Stand Motion With Stochastic Motion Planning Framework
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
Trajectory optimization has been an important approach in biomechanics for the analysis and prediction of the limb movement. Such approaches have paved the way for the motion planning of biped and quadruped robots as well. Most of these methods are deterministic, utilizing first-order iterative gradient-based algorithms incorporating the constrained differentiable objective functions. However, the limitation of prevailing methods concerning differentiability hinders the implementation of non-differentiable objective functions such as metabolic energy expenditure (MEE) function, which is highly relevant for physiological systems and can even be implemented across the muscular space. This paper consolidates the implementation of the prevalent direct collocation-based optimal control method with the stochastic trajectory optimization method based on Policy Improvement with Path Integral (PI2) for comprehending the human sit-to-stand (STS) motion. PI2 method, which utilizes reinforcement learning of Dynamic Movement Primitive (DMP) to learn a goal-based trajectory is implemented and validated by comparing with the experimental result in joint-space and muscle-space.