Dingyi211

Dingyi211's Stars

• philippwulff/TUM_RCI

  Lecture Notes for Robotics, Cognition, Intelligence @ TUM

  Language:TeX4514

• bzarr/TUM-CONTROL

  A modular and scalable simulation framework for ultra-rapid prototyping of self-adaptive, stochastic and robust Nonlinear Model Predictive Control for Autonomous Vehicle Motion Control

  Language:Python111

• matheecs/ocs2_legged_robot_notes

  Language:C++14835

• samholt/NeuralLaplaceControl

  Neural Laplace Control for Continuous-time Delayed Systems - an offline RL method combining Neural Laplace dynamics model and MPC planner to achieve near-expert policy performance in environments with irregular time intervals and an unknown constant delay.

  Language:Python94

• ZW628/Shenlan_Planning_Control_Course

  深蓝学院_规划控制课程_代码及资料

  Language:Makefile43

• Chenjq-99/deepblue_planning_control

  深蓝学院自动驾驶规划控制ROS1(melodic) + Carla0.9.13

  Language:Makefile134

• ApolloAuto/apollo

  An open autonomous driving platform

  Language:C++25k9.7k

• XiaojingGeorgeZhang/OBCA

  Optimization-Based Collision Avoidance - a path planner for autonomous navigation

  Language:Julia425152

• robotics-upo/nav2_social_costmap_plugin

  Plugin-based layer for social navigation in the Nav2 system of ROS2

  Language:C++218

• rst-tu-dortmund/costmap_converter

  A ros package that includes plugins and nodes to convert occupied costmap2d cells to primitive types

  Language:C++133103

• jginesclavero/social_nav2

  Language:C++293

• nirajbasnet/Nonlinear_MPCC_for_autonomous_racing

  Nonlinear MPCC for autonomous driving of F1/10 cars

  Language:Python7519

• Gandhi444/Nav2-RRTStar

  Implementation of RRT* algorithm in Nav2 for ros2 humble

  Language:Python51

• HiPeRT/ifac2020_f1tenth_submission

  Code used for the F1tenth virtual race at IFAC 2020

  Language:C++162

• neobotix/neo_mpc_planner2

  Omnidirectional planner for mobile robots based on MPC

  Language:C++322

• jianzhuozhuTHU/MPC-D-CBF

  The code will soon be open source.

  Language:C++15821

• HybridRobotics/cbf

  An open source repository for control, planning and navigation about control barrier functions.

  Language:Python15625

• GT-RIPL/Awesome-LLM-Robotics

  A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites

  2.7k223

• gundoganalperen/adp_rl

  Approximate Dynamic Programming and Reinforcement Learning - Programming Assignment

  Language:Python8

• HybridRobotics/car-racing

  A toolkit for testing control and planning algorithm for car racing.

  Language:Python16529

• Neilblaze/EI70360

  Academic Coursework on Machine Learning and Optimization [OML] — TUM

  Language:Jupyter Notebook4

• epfml/OptML_course

  EPFL Course - Optimization for Machine Learning - CS-439

  Language:Jupyter Notebook1.1k311

• matgrand/bfmc_2022

  Repository for Bosch Future Mobility Challenge 2022

  Language:Jupyter Notebook33

• pmusau17/Platooning-F1Tenth

  F1Tenth Simulation Code: Platooning, Computer Vision, Reinforcement Learning, Path Planning

  Language:HTML4923

• JZ76/f1tenth_simulator_two_agents

  This is a two-agents simulator for F1TENTH model car, already implemented model predictive control and recurrent neural network as controlling algorithm

  Language:PureBasic51

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python53.9k5.6k

• CL2-UWaterloo/f1tenth_ws

  A repository for autonomous racing written in ROS2, designed for the F1TENTH platform. Code can run both in the physical car, as well as simulation with custom launch files.

  Language:C++41178

• kausiksivakumar/Adaptive-Planning-with-Model-Predictive-Control

  MPCC for autonomous racing

  4

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  26.3k2.2k

• Jarvis03/Book-Doc

  books and docments

  551218