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Dec 6, 2022 · This letter presents a novel inverse optimal control (IOC) approach that can account for uncertainties in measurements and system models.
Abstract—This letter presents a novel inverse optimal control (IOC) approach that can account for uncertainties in measurements and system models.
Oct 22, 2024 · This study presents a novel inverse optimal control (IOC) approach that can account for uncertainties in measurements and system models.
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Aug 31, 2024 · This paper introduces an optimal control framework to address the inverse problem using a learned regularizer, with applications in image reconstruction.
Missing: Reproducing Uncertainties.
An Inverse Optimal Control Approach to Explain Human Arm Reaching ...
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Apr 3, 2018 · In this study, we utilize an Inverse Optimal Control (IOC) framework in order to find the combination of those internal models and how this ...
Putting perception into action with inverse optimal control for ...
pmc.ncbi.nlm.nih.gov › PMC9522207
Here, we introduce a computational analysis framework for continuous psychophysics based on Bayesian inverse optimal control.
Sep 5, 2022 · This method, called Inverse Optimal Control (IOC), is used to understand better the control that governs human movement. [5] and also in ...
Sep 29, 2022 · This important article presents a Bayesian model framework for estimating individual perceptual uncertainty from continuous tracking data.
An Inverse Optimal Control Approach for Learning and Reproducing Under Uncertainties. Article. Jan 2022. Sooyung Byeon · Dawei Sun · Inseok Hwang. This study ...
Feb 16, 2024 · In this paper, a novel methodology is introduced for the inverse optimal control of non-affine, nonlinear and discrete-time systems.