Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
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Updated
Jun 21, 2022 - Python
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
Open Source Optimization of Dynamic Multidisciplinary Systems
Implementation of the real-time MPC based on iLQR in Carla simulator
NASA's aircraft analysis, design, and optimization tool
iterative Linear Quadratic Regulator with constraints.
A toolkit for testing control and planning algorithm for car racing.
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.
Trajectory Planning and control
A pseudo-spectral collocation based multi-phase Optimal control problem solver
Trajectory optimization algorithms for robotic control.
A toolbox for trajectory optimization of dynamical systems
Model Predictive Control of a Flappy Bird Clone using Mixed Integer Programming
OpTaS: An optimization-based task specification library for trajectory optimization and model predictive control.
Functions and classes for gradient-based robot motion planning, written in Ivy.
Differential Dynamic Programming (DDP) with automatic symbolic differentiation
Implementing trajectory optimization on bipedal system
pyobca is a python implement of Optimization-Based Collision Avoidance path optimization (OBCA) algorithm
Leveraging Neural Network Gradients within Trajectory Optimization for Proactive Human-Robot Interactions
This repository is dedicated to studying the different trajectory planning methods (theory + practical).
Differentiable MPC in Chainer, developed as part of PFN summer internship 2019.
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