Noticias
icub-models
Official URDF and SDF models of the iCub humanoid robot.
IITHumanoid | DailyMecha
Explore investigaciones, noticias y demostraciones de Humanoid. Los resúmenes enlazan a las fuentes originales y distinguen resultados publicados de afirmaciones no verificadas.
Noticias
ROBOTIS-THORMANG-MPC
ROS packages for the motion of THORMANG3, MPC means Motion PC.
ROBOTISNoticias
ROBOTIS-OP3
ROS packages for the ROBOTIS OP3
ROBOTISNoticias
roboto_origin
Roboto_origin Fully Open-Source DIY Humanoid Robot/萝博头原型机全开源手搓级人形机器人
RoboPartyNoticias
microduck
A Tiny biped duck robot 🦆
Pollen RoboticsNoticias
nimbro-op
Sourcecode & CAD drawings of NimbRo-OP
University of BonnNoticias
ToddlerBot
toddlerbot
Stanford UniversityNoticias
berkeley-humanoid-lite
Codebase for Berkeley Humanoid Lite v1
UC BerkeleyNoticias
Open_Duck_Mini
Making a mini version of the BDX droid. https://discord.gg/UtJZsgfQGe
Open Duck research projectNoticias
AI Sapiens
ROBOTIS publishes ROS 2 packages for AI Sapiens, including controllers, hardware interfaces, robot descriptions and simulation support. The repository identifies Apache-2.0 as its root software license. This listing confirms the visible software packages; it does not imply that every hardware design, weight file or third-party dependency has the same license.
ROBOTISNoticias
Generative Bionics plans Italian Physical AI Data Factory for humanoids
Generative Bionics plans a 5,000-square-meter Physical AI Data Factory in Italy, targeted to become operational by Q4 2027. Fleets of its GENE.01 humanoid will perform industrial tasks in reproduced work environments, collecting vision, motion, and full-body tactile data. The company says physical data and digital-twin simulations will support training and validation before customer deployment; AMD is its planned AI infrastructure partner. The facility is an announced plan, not an operational site.
The Robot ReportInvestigación
Humanoid Mobility via Attention-based Contacts
The framework controls a Unitree G1 humanoid using an attention-based contact planner and a contact-conditioned whole-body tracker. Motion data serves only as a training prior; reinforcement-learning fine-tuning helps the policy handle terrain variations beyond the demonstrations. At deployment, it uses onboard observations without reference inputs, enabling one policy to perform tasks including ladder and stair climbing, crawling, vaulting, and stepping-stone traversal.
arXiv cs.RO