ArticleFrontiers in computational neuroscience2016
Predictive Simulation of Reaching Moving Targets Using Nonlinear Model Predictive Control.
Article in Frontiers in computational neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Human-Aware Control for Physically Interacting Robots.Bioengineering (Basel, Switzerland) · 2025Article
- Co-contraction embodies uncertainty: An optimal feedforward strategy for robust motor control.PLoS computational biology · 2024Article
- Continuous evaluation of cost-to-go for flexible reaching control and online decisions.PLoS computational biology · 2023Article
- Model-Based Mid-Level Regulation for Assist-As-Needed Hierarchical Control of Wearable Robots: A Computational Study of Human-Robot Adaptation.Robotics (Basel, Switzerland) · 2022Article
- Action planning and control under uncertainty emerge through a desirability-driven competition between parallel encoding motor plans.PLoS computational biology · 2021Article
- InverseMuscleNET: Alternative Machine Learning Solution to Static Optimization and Inverse Muscle Modeling.Frontiers in computational neuroscience · 2021Article
- Optimality Principles in Human Point-to-Manifold Reaching Accounting for Muscle Dynamics.Frontiers in computational neuroscience · 2020Article
- Article
- On the Relationship Between Muscle Synergies and Redundant Degrees of Freedom in Musculoskeletal Systems.Frontiers in computational neuroscience · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
This article investigates the application of optimal feedback control to trajectory planning in voluntary human arm movements. A nonlinear model predictive controller (NMPC) with a finite prediction horizon was used as the optimal feedback controller to predict the hand trajectory planning and execution of planar reaching tasks. The NMPC is completely predictive, and motion tracking or electromyography data are not required to obtain the limb trajectories. To present this concept, a two degree of freedom musculoskeletal planar arm model actuated by three pairs of antagonist muscles was used to simulate the human arm dynamics. This study is based on the assumption that the nervous system minimizes the muscular effort during goal-directed movements. The effects of prediction horizon length on the trajectory, velocity profile, and muscle activities of a reaching task are presented. The NMPC predictions of the hand trajectory to reach fixed and moving targets are in good agreement with the trajectories found by dynamic optimization and those from experiments. However, the hand velocity and muscle activations predicted by NMPC did not agree as well with experiments or with those found from dynamic optimization.
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