Highlights
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Task-Driven-Hybrid-Reduction Public
We developed a task-driven hybrid model reduction method for solving dexterous manipulation with 5 minutes of online learning.
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A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
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A framework and method to jointly learn a (neural) control objective function and a time-warping function only from sparse demonstrations or waypoints.
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Safe-PDP Public
Safe Pontryagin Differentiable Programming (Safe PDP) is a new theoretical and algorithmic safe differentiable framework to solve a broad class of safety-critical learning and control tasks.
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Learning-LCS Public
Forked from DAIRLab/Learning-LCSA new learning formulation/method to learn/identify a piecewise linear system, also named as linear complementarity system.
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A new method for a robot to learn a control objective from human user's directional corrections.
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Inverse optimal control from incomplete trajectory observations, proposing the concept of the recovery matrix which provides further insights into objective learning process.
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ioc Public
Forked from adaptivesystemslab/iocInverse optimal control codebase