List of resources about programming practices for writing safety-critical software.
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Updated
Apr 23, 2024 - Python
List of resources about programming practices for writing safety-critical software.
JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.
This repository provides a design methodology and approach to building highly-reliable applications on Microsoft Azure for mission-critical workloads.
NeurIPS 2023: Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmark
Matlab Interface for Control Barrier Function (CBF) and Control Lyapunov Function (CLF) based control methods.
Constant-complexity deterministic memory allocator (heap) for hard real-time high-integrity embedded systems. There is very little activity because the project is finished and does not require further changes.
Replacements to standard numeric types which throw exceptions on errors
🚀 A fast safe reinforcement learning library in PyTorch
A mixed-criticality platform built around Cheshire, with a number of safety/security and predictability features. Ready-to-use FPGA flow on multiple boards is available.
Fast and flexible data logging/tracing toolkit for software testing and debugging. Minimally intrusive C/C++ code instrumentation, host-based decoding application, demo code included.
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.
Official Code for Paper: Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
Safety-critical controllers for single/multi robotic navigation: CBF-QP, MPC-CBF, and etc.
The Verifiably Safe Reinforcement Learning Framework
Bourne shell, template engine, scripting language reliable, scalable projects. Based a ISO standard proven effective for large, mission-critical projects, SparForte is designed for fast development while, at the same time, providing easier designing, maintenance and bug removal. About 130.000 lines of code.
Repository containing the code for the paper "Safe Model-Based Reinforcement Learning using Robust Control Barrier Functions". Specifically, an implementation of SAC + Robust Control Barrier Functions (RCBFs) for safe reinforcement learning in two custom environments
A list of papers that studies out-of-distribution (OOD) detection and misclassification detection (MisD)
🚗 A repository for documenting and exploring the world of autonomous driving safety, featuring a curated collection of research papers, reports, and resource.
Bare Metal Board Support Package for Texas Instruments Cortex-R4F/R5F TMS570
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