tmacattank Goto Github PK

ego-planner

epsilon

eudm_planner

Implementation of the paper "Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching".

fast-planner

A Robust and Efficient Trajectory Planner for Quadrotors

fiss_planner

[RA-L 2022] FISS: A Trajectory Planning Framework using Fast Iterative Search and Sampling Strategy for Autonomous Driving

flarum-hack

frenet_optimal_planner

Implementation of the Frenet Optimal Planning Algorithm (with modifications) in ROS.

frenetix-occlusion

Code for Occlusion-aware Trajectory Planning

fucking-algorithm

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

gameformer

[ICCV 2023 Oral] Game-theoretic modeling and learning of Transformer-based interactive prediction and planning

gcopter

A General-Purpose Trajectory Optimizer for Multicopters

gcopter_homework

gcs-science-robotics

Motion Planning around Obstacles with Convex Optimization by Marcucci et al, 2023

gpir

[ICRA'22] Real-Time Trajectory Planning for Autonomous Driving with Gaussian Process and Incremental Refinement

gpmp2

Gaussian Process Motion Planner 2

grad_traj_optimization

Gradient-Based Online Safe Trajectory Generator

hpipm

High-performance interior-point-method QP solvers

icra2021

Source code of ICRA 2021 paper submission

ilqgames

Iterative Linear-Quadratic Games!

ilqr

iterative Linear Quadratic Regulator with constraints.

ilqr-1

Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models

interactive-motion-planning

ipopt

COIN-OR Interior Point Optimizer IPOPT

kino_sampling_with_regional_opti

learningbasedpredictionandplanning

this is a repo that constains the hw of the class.

lecture-notebooks-2023

limsim

LimSim: A Long-term Interactive Multi-scenario Traffic Simulator (ITSC 2023)

local_learning_cilqr

For the Paper Local Learning Enabled Iterative Linear Quadratic Regulator for Constrained Trajectory Planning

lucidgames.jl

machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接