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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Updated
Jul 23, 2022 - Python
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.
The Verifiably Safe Reinforcement Learning Framework
Code for the paper "Control Barriers in Bayesian Learning of System Dynamics"
Official code repository for "Integrating Predictive Motion Uncertainties with Distributionally Robust Risk-Aware Control for Safe Robot Navigation in Crowds"
Safe Control for Nonlinear Systems
Benchmark on interactive safety
Contains the code used to generate the results of the paper "Safe Control of Grid-Interfacing Inverters with Current Magnitude Limits"
Code for my bachelor thesis on "Control Barrier Functions for Learning-Based Regulation of Elastic Actuators with State Constraints".
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