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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript

Eclipse iceoryx™ - true zero-copy inter-process-communication

  • iceoryx
  • eclipse
  • ipc
  • inter-process-communication

:zap: The Mobile Robot Programming Toolkit (MRPT)

  • mrpt
  • c-plus-plus
  • mobile-robotics
  • slam

automatic differentiation made easier for C++

  • automatic-differentiation
  • auto-differentiation
  • autodiff
  • autodifferentiation

A memory allocator that automatically reduces the memory footprint of C/C++ applications.

  • allocator
  • memory
  • malloc-library
  • memory-allocator

open-appsec is a machine learning security engine that preemptively and automatically prevents threats against Web Application & APIs. This repo include the main code and logic.

The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control

  • optimal-control
  • model-predictive-control
  • ilqr
  • ilqg

Tesla Mod — Flipper Zero & ESP32. Nag killer, FSD region unlock, track mode, BMS dashboard, blind spot alert, high beam strobe, CAN capture, steering mode + more. Works via OBD-II or X179 connector.

  • automotive
  • can-bus
  • flipper-zero
  • flipper-zero-app

Robust and efficient coverage paths for autonomous agricultural vehicles. A modular and extensible Coverage Path Planning library

  • agriculture
  • autonomous-vehicles
  • coverage-path-planning
  • cpp17

Open Robotics Automation Virtual Environment: An environment for testing, developing, and deploying robotics motion planning algorithms.

An unofficial Android port of the Xbox 360 version of Grand Theft Auto IV created through the process of static recompilation

ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization.