q10l01p

q10l01p's Stars

• MCZhi/DTPP

  [ICRA 2024] Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning

  Language:Python10713

• RussTedrake/underactuated

  The course text for MIT 6.832 (and 6.832x on edX)

  Language:HTML703203

• google-deepmind/mujoco_mpc

  Real-time behaviour synthesis with MuJoCo, using Predictive Control

  Language:C++903132

• karpathy/LLM101n

  LLM101n: Let's build a Storyteller

  24k1.2k

• ethz-adrl/towr

  A light-weight, Eigen-based C++ library for trajectory optimization for legged robots.

  Language:C++877223

• abizovnuralem/go2_omniverse

  Unitree Go2, Unitree G1 support for Nvidia Isaac Lab (Isaac Gym / Isaac Sim)

  Language:Python17015

• isaac-sim/IsaacLabExtensionTemplate

  External extenstion template based on Orbit

  Language:Python459

• unitreerobotics/unitree_guide

  Language:C++18349

• felipemohr/Quadruped_CPG

  Quadruped Central Pattern Generator packages for ROS 2

  Language:C++2

• Tencent-RoboticsX/lifelike-agility-and-play

  Project Page for Lifelike Agility and Play in Quadrupedal Robots using Reinforcement Learning and Generative Pre-trained Models

  Language:Python414

• liuqh16/CloseAirCombat

  An environment based on JSBSIM aimed at one-to-one close air combat.

  Language:Python24177

• Improbable-AI/rapid-locomotion-rl

  Code for Rapid Locomotion via Reinforcement Learning

  Language:Python15036

• linhandev/dataset

  医学影像数据集列表 『An Index for Medical Imaging Datasets』

  2.4k347

• RS2002/Robot-mouse

  Repository for Final Design, "Motion Control Method for Small Quadruped Robots Based on Trajectory Modulation and Reinforcement Learning" (基于轨迹调制和强化学习的小型四足机器人运动控制方法)

  Language:Python1

• dyumanaditya/isaac-quad-loco

  Quadruped Locomotion learning through Reinforcement Learning and Model Predictive Control

  Language:Python9

• Robo-EX/Quadrupedal_Simulation_using_MATLAB

  Mobile Robotics has been evolving as one of the most promising domains in the field of Robotics. The ability of these robots to explore and maneuver in complex environments without human intervention attracts the attention of researchers across the globe. The mobile robots are classified into three different areas viz. wheeled robots, tracked robots, and legged robots. Robot locomotion system is an essential characteristic of mobile design, which depends not only on working space but also on technical measures like maneuverability, controllability, terrain condition, efficiency, and stability. Applications involving locomotion over rough terrains or disaster management where the robot is needed to access the remote areas within the debris demand the use of legged robots. Legged robots are further classified depending on the number of legs the robot has. Hence the types of legged robots are pogo-stick robots or one-legged robots, bi-pedal or two-legged robots, quadrupedal or four-legged robots, six-legged or hexapod robots, and eight-legged robots. Each of the types has unique applications and special locomotion mechanisms. The GAIT behavior of the quadrupedal robots is inspired by the quadruped animals like horses, dogs, etc. This project is focused on the Simulation & Control of a Quadrupedal Robot, using trajectory generation for the locomotion and describing three types of GAIT behaviors for the robot, viz. Walking, Trotting and Galloping. These are based on the speed and leg-movement patterns of the robots. These behaviors can be transitioned depending on the application and the terrain pattern. All the mechanisms are designed and simulated in MATLAB, and Simulink.

  Language:MATLAB183

• psrobotics/quadruped_bai_tiny

  A low-cost 8DOF torque controllable quadruped.

  Language:C++11310

• ziyanx02/multiagent-quadruped-environment

  A multi-agent quadruped environment, supporting learning of locomotion control or merely high-level planning.

  Language:Python36

• awesomericky/multiple-gait-controller-for-quadruped-robot

  Learning multiple gaits of quadruped robot using hierarchical reinforcement learning

  Language:Python368

• ShuoYangRobotics/A1-QP-MPC-Controller

  An open source implementation of MIT Cheetah 3 controllers

  Language:C++588126

• yxyang/fast_and_efficient

  Language:Python6717

• chengxuxin/extreme-parkour

  ICRA 2024: Train your parkour robot in less than 20 hours.

  Language:Python48689

• MAVProxyUser/YushuTechUnitreeGo1

  宇树科技 Yushu Technology (Unitree) go1 development notes

  Language:TeX27071

• MiladShafiee/DeepTransition

  Learning Agile Quadrupedal Locomotion on Challenging Terrains

  Language:Python343

• awesomericky/quadruped-robot-belief-encoder

  Implementation of some core elements of "Learning robust perceptive locomotion for quadrupedal robots in the wild"

  Language:Python212

• curieuxjy/Awesome_Quadrupedal_Robots

  Awesome Quadrupedal Robots

  Language:Python45557

• metadriverse/policydissect

  [NeurIPS 2022] Official implementation of the paper: "Human-AI Shared Control via Policy Dissection"

  Language:Python485

• mit-biomimetics/ORCAgym

  phase-based Observations, Rewards, Coupling Ablation

  Language:Python325

• mit-biomimetics/pkGym

  Language:Python71

• LeCAR-Lab/ABS

  Language:Python15411