Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
- Updated
Jun 21, 2022 - Python
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
Python implementation of an automatic parallel parking system in a virtual environment, including path planning, path tracking, and parallel parking
[RA-Letter 2023] RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments
iterative Linear Quadratic Regulator with support for constraints on input and state variables via barrier functions—Numba-accelerated.
Assetto Corsa OpenAI Gym Environment
Unofficial implementaton of the paper DTC: Deep Tracking Control
J. Berberich, J. Köhler, M. A. Müller and F. Allgöwer, "Data-Driven Model Predictive Control With Stability and Robustness Guarantees," in IEEE Transactions on Automatic Control, vol. 66, no. 4, pp. 1702-1717, April 2021, doi: 10.1109/TAC.2020.3000182.
A rigid-tube based robust MPC python package.
Code for the paper Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization
Differential Dynamic Programming (DDP) with automatic symbolic differentiation
Model Predictive Controller tested on Carla simulator on Race track with reference velocity.
MPC Locomotion controller implemented on Unitree Go2 quadruped in MuJoCo
A hybrid collision avoidance system combining Deep Reinforcement Learning with Model Predictive Control, designed for autonomous vehicles in CARLA to navigate scenarios with stationary obstacles.
RRT*-MPC path planning for spacecraft navigation in dynamic environment. Graded project for the ETH course "Planning and Decision Making for Autonomous Robots".
Pytorch implementation of Model Predictive Control with learned models
Python package for model predictive control (MPC) for EPASWMM5 models
This repository contains the code for our paper on Dynamic Mirror Descent based MPC for Model-Free RL
Learning Model Predictive Control (LMPC) for autonomous racing in CARLA 3D environment.
A code for implementing autonomous car software, including environment perception, lanes detection, identifying traffic signs, and controlling the vehicle with digital PID.
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