Dev
GitHub repos gaining traction - what high-signal users are starring and what's climbing the board, captured daily and enriched from GitHub. Raw material for spotting new tech and patterns worth building on.
3,195
repos tracked
105
surfaced this week
193
created < 30d
Python
top language
41 repos
-
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
-
Unified framework for robot learning with multi-physics/renderer support
-
Web-based MuJoCo viewer powered by Viser
-
Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research
-
Gym-Anything for Robotics: framework and the RoboWorld benchmark
-
StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing
-
A Tiny biped duck robot 🦆
-
The first exam for code agents in the physical world: frozen robot tasks from many benchmark suites, each answered with a program and verified in a separate sandbox. Runs on Harbor.
-
An open interactive toolkit that accelerates human and agentic physics-based Real2Sim of Robot Manipulation Tasks
-
Exact convex collision geometry for MuJoCo assemblies: pegs and holes from any outline, threads, and gears.
-
OpenTac: open tools to design, fabricate, read and simulate flex-PCB tactile skins that sense normal and shear force, for any robot surface.
-
🦀 Jumper — an crab robot.
-
Official code for the SEAR benchmark
-
RL training environments for Microduck (mjlab)
-
The ultimate harness for coding agents and beyond. All your agents. All your machines. One command center. Start with code, then follow your curiosity and build across disciplines: CAD, circuits, robots, games and music.
-
Evidence-backed, model-agnostic runtime contracts for physical agents
-
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
-
GPT-6 Astra for embodied AI and robotics.
-
An mjlab integration for the Booster K1
-
A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.
-
A library of experiments using frontier LLMs/VLMs for robotics tasks, currently focusing on GPT-6 Astra.
-
Reproducible Microduck RL experiments, policies, simulation assets, and hardware add-ons
-
Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson
-
SuperDex brings together a purpose-built physics engine, robotics authoring tools, and a scalable reinforcement learning interface in a unified simulation platform, with VR-based teleoperation and additional capabilities planned for future releases.
-
A curated list of software, simulators, policies, agent tools and coverage for the Pollen Robotics / Hugging Face Microduck robot
-
A Simple Transport Layer For Teleoperation And Inference
-
🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning
-
Reinforcement Learning (RL) environments for the Microban platform, a 30cm open-source and affordable humanoid robot.
-
Microban is an affordable, fully 3D-printable, and 100% open-source humanoid robot. Powered by a Raspberry Pi Zero 2W and 19 Dynamixel servomotors, it serves as an accessible DIY platform for learning, experimentation, and research in robotics.
-
Python-first native robotics simulation and reinforcement-learning environments
-
DART: Dynamic Animation and Robotics Toolkit
-
Official code repository for the paper "Hallucination in World Models is Predictable and Preventable".
-
[CoRL 2026] Official Repository for: Scaling Self-Play for End-to-End Driving
-
One policy. Any motion. Train universal whole-body tracking in mjlab—swap clips, not checkpoints.
-
ABC: Scalable Behavior Cloning with Open Data, Training, and Evaluation
-
Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research.
-
RL training environments for dexhand tasks (mjlab)
-
Multi-Joint dynamics with Contact. A general purpose physics simulator.
-
Predictive Style Matching (PSM), is method in which an offline predictor maps the robot’s lower-body state history and velocity commands to interpretable upper-body joint and gait targets that shape the rewards during training.
-
FastCrest Tether: the OSS edge-to-cloud AI deploy CLI. Optimize, verify, deploy across Jetson, RTX, Apple Silicon, AMD. Hybrid edge-cloud inference with parity certs.