Topic: "robot-learning"
isaac-sim/IsaacLab
Unified framework for robot learning built on NVIDIA Isaac Sim
Language: Python - Size: 302 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 3,989 - Forks: 1,902
haosulab/ManiSkill
SAPIEN Manipulation Skill Framework, an open source GPU parallelized robotics simulator and benchmark, led by Hillbot, Inc.
Language: Python - Size: 860 MB - Last synced at: 4 days ago - Pushed at: 8 days ago - Stars: 1,756 - Forks: 296
ARISE-Initiative/robosuite
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
Language: Python - Size: 601 MB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 1,752 - Forks: 548
robotlearning123/awesome-isaac-gym
A curated list of awesome NVIDIA Issac Gym frameworks, papers, software, and resources
Size: 7.94 MB - Last synced at: 2 days ago - Pushed at: 2 months ago - Stars: 972 - Forks: 73
robocasa/robocasa
RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
Language: Python - Size: 16.7 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 816 - Forks: 88
abizovnuralem/go2_omniverse
Unitree Go2, Unitree G1 support for Nvidia Isaac Lab (Isaac Gym / Isaac Sim)
Language: Python - Size: 1.13 GB - Last synced at: 6 days ago - Pushed at: 29 days ago - Stars: 723 - Forks: 57
Skylark0924/Rofunc
š¤ The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation
Language: Python - Size: 1.01 GB - Last synced at: 29 days ago - Pushed at: about 1 month ago - Stars: 624 - Forks: 55
vikashplus/robohive
A unified framework for robot learning
Language: Python - Size: 126 MB - Last synced at: about 10 hours ago - Pushed at: 7 months ago - Stars: 580 - Forks: 89
notmahi/dobb-e
DobbĀ·E: An open-source, general framework for learning household robotic manipulation
Language: G-code - Size: 52.7 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 571 - Forks: 52
simpler-env/SimplerEnv
Evaluating and reproducing real-world robot manipulation policies (e.g., RT-1, RT-1-X, Octo) in simulation under common setups (e.g., Google Robot, WidowX+Bridge) (CoRL 2024)
Language: Jupyter Notebook - Size: 16.5 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 555 - Forks: 76
clvrai/furniture
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
Language: Python - Size: 671 MB - Last synced at: 7 months ago - Pushed at: over 2 years ago - Stars: 503 - Forks: 55
OpenDriveLab/UniVLA
[RSS 2025] Learning to Act Anywhere with Task-centric Latent Actions
Language: Python - Size: 2.85 MB - Last synced at: 4 days ago - Pushed at: 6 days ago - Stars: 457 - Forks: 21
Lifelong-Robot-Learning/LIBERO
Benchmarking Knowledge Transfer in Lifelong Robot Learning
Language: Jupyter Notebook - Size: 308 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 389 - Forks: 65
jimmyyhwu/tidybot2
TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
Language: Python - Size: 2.77 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 270 - Forks: 25
kindredresearch/SenseAct
SenseAct: A computational framework for developing real-world robot learning tasks
Language: Python - Size: 87 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 207 - Forks: 40
isri-aist/RoboManipBaselines
A software framework integrating various imitation learning methods and benchmark environments for robotic manipulation
Language: Python - Size: 88.4 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 204 - Forks: 28
NathanWu7/isaacLab.manipulation
An independent extension based on IsaacLab. It provides support for Robot Manipulation tasks (Robot Arm and Dextrous Hand).
Language: Python - Size: 7.63 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 183 - Forks: 21
clvrai/furniture-bench
FurnitureBench: Real-World Furniture Assembly Benchmark (RSS 2023)
Language: Python - Size: 170 MB - Last synced at: 17 days ago - Pushed at: 3 months ago - Stars: 180 - Forks: 21
clvrai/spirl
Official implementation of "Accelerating Reinforcement Learning with Learned Skill Priors", Pertsch et al., CoRL 2020
Language: Python - Size: 16.6 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 165 - Forks: 32
H-Freax/Awesome-Video-Robotic-Papers
This repository compiles a list of papers related to the application of video technology in the field of robotics! Starā the repo and follow me if you like what you seeš¤©.
Size: 46.9 KB - Last synced at: 3 days ago - Pushed at: 5 months ago - Stars: 161 - Forks: 6
HaoyiZhu/SPA
[ICLR 2025] SPA: 3D Spatial-Awareness Enables Effective Embodied Representation
Language: Python - Size: 10.2 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 154 - Forks: 6
rewarped/rewarped
Reinforcement learning in differentiable multiphysics simulation with NVIDIA Warp.
Language: Python - Size: 2.23 MB - Last synced at: 9 days ago - Pushed at: 24 days ago - Stars: 134 - Forks: 13
RayYoh/Awesome-Robot-Learning
This repo contains a curative list of robot learning (mainly for manipulation) resources.
Size: 6.02 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 132 - Forks: 5
RobustFieldAutonomyLab/DRL_graph_exploration
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs
Language: C++ - Size: 239 MB - Last synced at: about 1 month ago - Pushed at: almost 4 years ago - Stars: 130 - Forks: 19
UT-Austin-RPL/GIGA
Official PyTorch implementation of Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
Language: Python - Size: 163 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 126 - Forks: 23
NVlabs/oscar
Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
Language: Python - Size: 191 MB - Last synced at: 15 days ago - Pushed at: about 3 years ago - Stars: 123 - Forks: 17
jonzamora/awesome-robot-learning-envs
A list of awesome and popular robot learning environments
Size: 224 MB - Last synced at: 4 days ago - Pushed at: 10 months ago - Stars: 110 - Forks: 1
RobustFieldAutonomyLab/DRL_robot_exploration
Self-Learning Exploration and Mapping for Mobile Robots via Deep Reinforcement Learning
Language: Python - Size: 278 MB - Last synced at: about 5 hours ago - Pushed at: almost 5 years ago - Stars: 94 - Forks: 17
Aaditya-Prasad/consistency-policy
[RSS 2024] Consistency Policy: Accelerated Visuomotor Policies via Consistency Distillation
Language: Python - Size: 13.6 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 81 - Forks: 5
ai4ce/CityWalker
[CVPR 2025] CityWalker: Learning Embodied Urban Navigation from Web-Scale Videos
Language: Python - Size: 82.8 MB - Last synced at: 2 months ago - Pushed at: 3 months ago - Stars: 75 - Forks: 5
RayYoh/OCRM_survey
A Survey of Embodied Learning for Object-Centric Robotic Manipulation
Size: 1.21 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 71 - Forks: 4
zhouzypaul/auto_eval
AutoEval: Autonomous Evaluation of Generalist Robot Manipulation Policies in the Real World
Language: Python - Size: 1.04 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 70 - Forks: 4
Weixy21/BarrierNet
Safe robot learning
Language: Python - Size: 3.65 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 70 - Forks: 18
NVlabs/ACID
ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
Language: Python - Size: 3.04 MB - Last synced at: 15 days ago - Pushed at: about 3 years ago - Stars: 69 - Forks: 7
UT-Austin-RPL/maple
Official codebase for Manipulation Primitive-augmented reinforcement Learning (MAPLE)
Language: Python - Size: 14.7 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 68 - Forks: 12
Improbable-AI/airobot
A python library for robot learning - An extension to PyRobot
Language: Python - Size: 67.6 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 67 - Forks: 23
luccachiang/robots-pretrain-robots
[ICLR 2025š] This is the official implementation of paper "Robots Pre-Train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets".
Language: Python - Size: 5.78 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 64 - Forks: 1
mikeroyal/Robotics-guide
Robotics Guide
Language: Python - Size: 212 KB - Last synced at: 12 days ago - Pushed at: over 1 year ago - Stars: 63 - Forks: 13
clvrai/mopa-rl
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments (CoRL 2020)
Language: Python - Size: 251 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 63 - Forks: 11
ChengshuLi/HRL4IN
Code for CoRL 2019 paper: HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators
Language: Python - Size: 83 KB - Last synced at: 20 days ago - Pushed at: almost 4 years ago - Stars: 62 - Forks: 13
JadeCong/Awesome-Robot-Learning
Awesome Lists about Robot Learning.
Size: 116 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 61 - Forks: 2
rrahmati/roboinstruct-2
Train a robot to see the environment and autonomously perform different tasks
Language: C++ - Size: 1.32 MB - Last synced at: 14 days ago - Pushed at: over 7 years ago - Stars: 49 - Forks: 14
SafeRL-Lab/Robust-Gymnasium
[ICLR 2025] Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning.
Language: Python - Size: 310 MB - Last synced at: 29 days ago - Pushed at: 3 months ago - Stars: 48 - Forks: 2
pantor/griffig
Robotic Manipulation - Learned in the Real World
Language: Python - Size: 739 KB - Last synced at: 2 months ago - Pushed at: almost 4 years ago - Stars: 48 - Forks: 10
AndrejOrsula/space_robotics_bench
Benchmark for Space Robotics
Language: Python - Size: 2.91 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 47 - Forks: 5
MohitShridhar/genima
Official Code Repo for GENIMA
Language: Python - Size: 5.48 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 45 - Forks: 0
UT-Austin-RPL/BUDS
Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation (BUDS)
Language: Python - Size: 106 KB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 41 - Forks: 6
42jaylonw/shifu
Lightweight Isaac Gym Environment Builder
Language: Python - Size: 31.6 MB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 37 - Forks: 2
inspirai/MetalHead
Natural Locomotion, Jumping and Recovery of Quadruped Robot A1 with AMP
Language: Python - Size: 68.1 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 34 - Forks: 1
OpenDriveLab/FreeTacMan
FreeTacMan: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation
Language: Python - Size: 59.9 MB - Last synced at: 8 days ago - Pushed at: 17 days ago - Stars: 30 - Forks: 0
minliu01/SoftMAC
Code repository for our paper SoftMAC: Differentiable Soft Body Simulation with Forecast-based Contact Model and Two-way Coupling with Articulated Rigid Bodies and Clothes
Language: Python - Size: 64.2 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 30 - Forks: 4
clvrai/skimo
Skill-based Model-based Reinforcement Learning (CoRL 2022)
Language: Python - Size: 50.2 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 30 - Forks: 4
UT-Austin-RPL/sirius
Official codebase for Sirius: Robot Learning on the Job
Language: Python - Size: 146 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 28 - Forks: 3
emNavi/AirGym
A high-performance quadrotor deep reinforcement learning platform built upon IsaacGym.
Language: Python - Size: 180 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 26 - Forks: 1
Xiaohui9607/physical_interaction_video_prediction_pytorch
Based on Chealsea Finn's et al "Unsupervised Learning for Physical Interaction through Video Prediction"
Language: Python - Size: 46.9 KB - Last synced at: over 2 years ago - Pushed at: almost 5 years ago - Stars: 26 - Forks: 4
NZ-Liam-Zhong/Awesome_AI_for_Robotics_Learning_Notes
These are my learning notes about robot learning and Embodied AI[å ·čŗ«ęŗč½å¦ä¹ ē¬č®°]. If you feel it hard to learn them, please star me!
Size: 1.31 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 22 - Forks: 3
Boey-li/AdaptiGraph
[RSS24] AdaptiGraph: Material-Adaptive Graph-Based Neural Dynamics for Robotic Manipulation
Language: C++ - Size: 74.7 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 22 - Forks: 1
HaoyiZhu/PointCloudMatters
Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning
Language: Python - Size: 4.95 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 19 - Forks: 0
clvrai/skill-chaining
Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization (CoRL 2021)
Language: Python - Size: 8.81 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 18 - Forks: 2
xiaoxiaoxh/DeformPAM
[ICRA 2025] DeformPAM: Data-Efficient Learning for Long-horizon Deformable Object Manipulation via Preference-based Action Alignment
Language: Python - Size: 8.37 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 17 - Forks: 1
taochenshh/hcp
(NeurIPS 2018) Hardware Conditioned Policies for Multi-Robot Transfer Learning
Language: Python - Size: 1.19 MB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 17 - Forks: 7
MCG-NJU/TPM
[WACV 2025 Oral] Transferring Foundation Models for Generalizable Robotic Manipulation
Language: Python - Size: 2.12 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 15 - Forks: 0
med-air/ViSkill
[IROS 2023] Value-Informed Skill Chaining for Policy Learning of Long-Horizon Tasks with Surgical Robot
Language: Python - Size: 333 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 11 - Forks: 0
yuechen0614/ET-SEED
[ICLR 2025š] Official implementation for paper "ET-SEED: Efficient Trajectory-Level SE(3) Equivariant Diffusion Policy".
Language: Python - Size: 185 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 11 - Forks: 0
Evan-wyl/robotlearning
Papers, codes, datasets, applications, tutorials.
Size: 113 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 11 - Forks: 0
wanxinjin/Learning-from-Directional-Corrections
A new method for a robot to learn a control objective from human user's directional corrections.
Language: Python - Size: 168 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 11 - Forks: 2
JunfengChen-robotics/MultiRoboLearn
This is a software which can by used by researcher multi-agent reinforcement learning in robot learning for multi-robot system
Language: Python - Size: 50.6 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 11 - Forks: 5
lstrgar/ELDiR
Code for "Evolution and learning in differentiable robots", Strgar et al, proceedings of Robotics: Science and Systems 2024
Language: Jupyter Notebook - Size: 20.9 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 10 - Forks: 1
Derek-TH-Wang/hybrid_gait
RL training for quadruped robot(mit minicheetah) various gaits in different velocity based on MPC controller.
Language: C++ - Size: 16.6 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 10 - Forks: 2
bhairavmehta95/asymmetric-actor-critic
Implementation of Asymmetric Actor Critic for Image-Based Robot Learning in Tensorflow.
Language: Python - Size: 67.4 KB - Last synced at: over 2 years ago - Pushed at: about 6 years ago - Stars: 10 - Forks: 7
GT-RAIL/clamp
Combined Learning from Demonstration and Motion Planning
Language: MATLAB - Size: 228 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 10 - Forks: 6
lefterisloukas/practical-rl
My solutions to the Practical Reinforcement Learning course by Coursera/HSE.
Language: Jupyter Notebook - Size: 17.3 MB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 9 - Forks: 8
andreaprotopapa/sofa-dr-rl
Enabling Faster Training of Robust Reinforcement Learning Policies for Soft Robots
Language: Python - Size: 297 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 8 - Forks: 2
andreaprotopapa/dr-soro
Domain Randomization for Robust, Affordable and Effective Closed-loop Control of Soft Robots
Size: 72.5 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 7 - Forks: 0
PietroVitiello/ActionRepresentation
MSc Project aimed at finding an alternative way of representing robot actions. We evaluate several machine learning models to control a simulated 7-joint robotic arm using solely a wrist mounted camera as input.
Language: Python - Size: 154 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 7 - Forks: 1
Aryia-Behroziuan/Robot-learning
In developmental robotics, robot learning algorithms generate their own sequences of learning experiences, also known as a curriculum, to cumulatively acquire new skills through self-guided exploration and social interaction with humans. These robots use guidance mechanisms such as active learning, maturation, motor synergies and imitation. Association rules Main article: Association rule learning See also: Inductive logic programming Association rule learning is a rule-based machine learning method for discovering relationships between variables in large databases. It is intended to identify strong rules discovered in databases using some measure of "interestingness".[60] Rule-based machine learning is a general term for any machine learning method that identifies, learns, or evolves "rules" to store, manipulate or apply knowledge. The defining characteristic of a rule-based machine learning algorithm is the identification and utilization of a set of relational rules that collectively represent the knowledge captured by the system. This is in contrast to other machine learning algorithms that commonly identify a singular model that can be universally applied to any instance in order to make a prediction.[61] Rule-based machine learning approaches include learning classifier systems, association rule learning, and artificial immune systems. Based on the concept of strong rules, Rakesh Agrawal, Tomasz ImieliÅski and Arun Swami introduced association rules for discovering regularities between products in large-scale transaction data recorded by point-of-sale (POS) systems in supermarkets.[62] For example, the rule {\displaystyle \{\mathrm {onions,potatoes} \}\Rightarrow \{\mathrm {burger} \}}\{{\mathrm {onions,potatoes}}\}\Rightarrow \{{\mathrm {burger}}\} found in the sales data of a supermarket would indicate that if a customer buys onions and potatoes together, they are likely to also buy hamburger meat. Such information can be used as the basis for decisions about marketing activities such as promotional pricing or product placements. In addition to market basket analysis, association rules are employed today in application areas including Web usage mining, intrusion detection, continuous production, and bioinformatics. In contrast with sequence mining, association rule learning typically does not consider the order of items either within a transaction or across transactions. Learning classifier systems (LCS) are a family of rule-based machine learning algorithms that combine a discovery component, typically a genetic algorithm, with a learning component, performing either supervised learning, reinforcement learning, or unsupervised learning. They seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions.[63] Inductive logic programming (ILP) is an approach to rule-learning using logic programming as a uniform representation for input examples, background knowledge, and hypotheses. Given an encoding of the known background knowledge and a set of examples represented as a logical database of facts, an ILP system will derive a hypothesized logic program that entails all positive and no negative examples. Inductive programming is a related field that considers any kind of programming language for representing hypotheses (and not only logic programming), such as functional programs. Inductive logic programming is particularly useful in bioinformatics and natural language processing. Gordon Plotkin and Ehud Shapiro laid the initial theoretical foundation for inductive machine learning in a logical setting.[64][65][66] Shapiro built their first implementation (Model Inference System) in 1981: a Prolog program that inductively inferred logic programs from positive and negative examples.[67] The term inductive here refers to philosophical induction, suggesting a theory to explain observed facts, rather than mathematical induction, proving a property for all members of a well-ordered set. Models Performing machine learning involves creating a model, which is trained on some training data and then can process additional data to make predictions. Various types of models have been used and researched for machine learning systems. Artificial neural networks Main article: Artificial neural network See also: Deep learning An artificial neural network is an interconnected group of nodes, akin to the vast network of neurons in a brain. Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one artificial neuron to the input of another. Artificial neural networks (ANNs), or connectionist systems, are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems "learn" to perform tasks by considering examples, generally without being programmed with any task-specific rules. An ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it. In common ANN implementations, the signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called "edges". Artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly after traversing the layers multiple times. The original goal of the ANN approach was to solve problems in the same way that a human brain would. However, over time, attention moved to performing specific tasks, leading to deviations from biology. Artificial neural networks have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis. Deep learning consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.[68]
Size: 2.93 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 7 - Forks: 0
prabinrath/xmop
[ICRA 2025] XMoP: Whole-Body Control Policy for Zero-shot Cross-Embodiment Neural Motion Planning
Language: Python - Size: 611 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 6 - Forks: 0
clvrai/mopa-pd
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation (CoRL 2021)
Language: Python - Size: 19.7 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 6 - Forks: 2
SarthakJShetty/tfn-robot
This repository hosts the physical robot code for ToolFlowNet. Published at CoRL '22.
Language: Python - Size: 33 MB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 5 - Forks: 0
gabrieletiboni/paintnet
PaintNet: Unstructured Multi-Path Learning from 3D Point Clouds for Robotic Spray Painting
Language: Python - Size: 31.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 5 - Forks: 1
wangcongrobot/Robot-Learning-From-Scratch
How to train a robot to learn skills from scratch
Language: Python - Size: 4.15 MB - Last synced at: over 2 years ago - Pushed at: about 5 years ago - Stars: 5 - Forks: 3
navigator8972/vae_assoc
Associative Variational Auto-encoders
Language: Python - Size: 966 KB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 5 - Forks: 3
yash-goel/reading-list
For Robotics and Robot Learning Resources
Size: 105 KB - Last synced at: almost 2 years ago - Pushed at: about 6 years ago - Stars: 5 - Forks: 3
AshishMehtaIO/Quadruped-robot-DQN
Language: C - Size: 73.2 KB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 4 - Forks: 0
zhanpenghe/SoftQLearning
Implementation of Soft QLearning Algorithm
Language: Python - Size: 7.81 KB - Last synced at: 4 months ago - Pushed at: about 7 years ago - Stars: 4 - Forks: 0
MCG-NJU/Tra-MoE
[CVPR 2025] Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning
Language: Python - Size: 231 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 3 - Forks: 0
JadeCong/Robotic-Softbody-Manipulation
Softbody Mainpulation for Robot based on DRL.
Language: Python - Size: 63.8 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 3 - Forks: 1
Xiaohui9607/mmvp
Visual Next-Frame Prediction using Multisensory Perception for Embodied Agents
Language: Python - Size: 33.9 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0
SoheilKhatibi/Webots-Image-Dataset-Collector
Webots Image Dataset Collection For Computer Vision And Deep Learning
Language: C++ - Size: 39.1 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0
mengyuest/stl_npc
[ICRA2024] A differentiable robot learning framework for task specifications and controller synthesis.
Language: Python - Size: 7.98 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 1
Ramtin92/mmvp
Visual Next-Frame Prediction using Multisensory Perception for Embodied Agents
Language: Python - Size: 5 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 1
MAdeelArshad/picnui-reactserver
The front-end design on React for PICNUI project to train the cobot using 3d TensorFlow pose estimation robot tracking
Language: JavaScript - Size: 2.81 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 1
domingoesteban/robolearn_envs
A Python package with OpenAI-Gym-like environments for Robot Learning
Language: Python - Size: 75.9 MB - Last synced at: almost 2 years ago - Pushed at: about 6 years ago - Stars: 2 - Forks: 2
ashwinreddy/rlg
Robot Learning Gym
Language: Python - Size: 27.9 MB - Last synced at: 8 months ago - Pushed at: over 8 years ago - Stars: 2 - Forks: 0
oadamharoon/text2nav
Minimalist framework for language-guided robot navigation using frozen vision-language embeddings. Achieves 74% success rate without fine-tuning. RSS 2025 Workshop paper.
Language: Python - Size: 182 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 1 - Forks: 0
pranay-junare/clothbot
Cloth Manipulation using self-supervised Spatial Action Maps
Language: C++ - Size: 71.1 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0
tongzhoumu/s2v-dagger
Code for "When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?"
Language: Python - Size: 321 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0
am-shb/evobots
A quadruped robot learns to control its joints to move towards an objective using genetic algorithm.
Language: Python - Size: 12.7 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0
domingoesteban/robolearn
A Python package for Robot Learning
Language: Jupyter Notebook - Size: 165 MB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 1
abhishekpadalkar/r_n_d_report
Language: TeX - Size: 20 MB - Last synced at: 7 days ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 3
