HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems

paper_quality_plot.matlab

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Fast symbolic computation, code generation, and nonlinear optimization for robotics

Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)

This is the official implementation of "Optimizing Large-Scale Fleet Management on a Road Network using Multi-Agent Deep Reinforcement Learning with Graph Neural Network" (ITSC 2021)

Model Predictive Contouring Controller (MPCC) for Autonomous Racing

SOTA Semantic Segmentation Models in PyTorch

PyTorch implementation of DreamerV2 model-based RL algorithm

Python sample codes for robotics algorithms.

A script that applies the AdaIN style transfer method to arbitrary datasets

Trajectory Planner in Multi-Agent and Dynamic Environments

Repository for studying distributional rl

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch