Humanoid Robot Bootcamp (Spain, November 25–27) — Onsite Training
Humanoid Robot Bootcamp (Spain, November 25–27) — Onsite Training
The ROS community is being informed of a three-day Humanoid Robot Reinforcement Learning Bootcamp taking place in Barcelona from November 25 to 27, 2026. Organized by The Construct Robotics Institute, the event focuses on practical implementation of reinforcement learning for humanoid systems. Participants will engage with sim-to-real pipelines using Isaac Lab and MuJoCo, whole-body control, motion imitation, teleoperation, and VLA models with Gr00t. Training includes validation in simulation followed by deployment on real Unitree G1 robots. The curriculum covers RL-based walking control, vision-language-action models, and practical experimentation sessions.
This announcement describes a three-day onsite training event in Barcelona scheduled for November 25–27, 2026, organized by The Construct Robotics Institute to teach reinforcement learning workflows for humanoid robots, including sim-to-real deployment on Unitree G1 units.
Source: ROS Discourse — Community updates · Read original article ↗
Article text · Original source · English
Hi ROS community,
We are organizing a 3-day Humanoid Robot Reinforcement Learning Bootcamp in Barcelona (November 25–27, 2026), focused on practical workflows for training and deploying control policies on humanoid robots.
The training is delivered by The Construct Robotics Institute and is designed for engineers and researchers interested in reinforcement learning applied to humanoid systems.
During the bootcamp, participants will work through the main components of a sim-to-real pipeline:
-
RL-based walking control using Isaac Lab and MuJoCo
-
Whole-body control and motion imitation
-
Teleoperation and imitation learning with Isaac Mimic
-
Vision-Language-Action (VLA) models with Gr00t
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Sim-to-sim validation and deployment on real robots
Humanoid Robot Reinforcement Learning Bootcamp DSCF16036240×3512 478 KB
Humanoid Robot Reinforcement Learning Bootcamp DSCF15376240×3512 468 KB
Participants will train and validate policies in simulation and deploy them on real humanoid robots (Unitree G1).
The format is fully practical, with all sessions focused on implementation and experimentation.
If relevant to your work, more details are available here: https://www.theconstruct.ai/humanoid-robot-reinforcement-learning-training/
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Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
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rticipants will work through the main components of a sim-to-real pipeline: RL-based walking control using Isaac Lab and MuJoCo Whole-body control and motion imitation Teleoperation and imitation learning with Isaac Mimic Vision-Language-Action (VLA) models with Gr00t Sim-to-sim validation and deployment on real robots Humanoid Robot Reinforcement Learning Bootcamp DSCF1603 6240×3512 478 KB Humanoid Robot Reinforceme
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rticipants will work through the main components of a sim-to-real pipeline: RL-based walking control using Isaac Lab and MuJoCo Whole-body control and motion imitation Teleoperation and imitation learning with Isaac Mimic Vision-Language-Action (VLA) models with Gr00t Sim-to-sim validation and deployment on real robots Humanoid Robot Reinforcement Learning Bootcamp DSCF1603 6240×3512 478 KB Humanoid Robot Reinforceme
Open source S3image resolution width
6,240
View original evidence
nt Learning Bootcamp DSCF1537 6240×3512 468 KB Participants will train and validate policies in simulation and deploy them on real humanoid robots (Unitree G1). The format is fully practical, with all sessions focused on implementation and experimentation. If relevant to your work, more details are available here: https://www.theconstruct.ai/humanoid-robot-reinforcement-learning-training/
Open source S4image resolution height
3,512
View original evidence
nt Learning Bootcamp DSCF1537 6240×3512 468 KB Participants will train and validate policies in simulation and deploy them on real humanoid robots (Unitree G1). The format is fully practical, with all sessions focused on implementation and experimentation. If relevant to your work, more details are available here: https://www.theconstruct.ai/humanoid-robot-reinforcement-learning-training/
Open source S4image file size
478
View original evidence
rticipants will work through the main components of a sim-to-real pipeline: RL-based walking control using Isaac Lab and MuJoCo Whole-body control and motion imitation Teleoperation and imitation learning with Isaac Mimic Vision-Language-Action (VLA) models with Gr00t Sim-to-sim validation and deployment on real robots Humanoid Robot Reinforcement Learning Bootcamp DSCF1603 6240×3512 478 KB Humanoid Robot Reinforceme
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- paper: not_reported
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Automatically extracted; no manual editorial approval recorded.
Hi ROS community, We are organizing a 3-day Humanoid Robot Reinforcement Learning Bootcamp in Barcelona (November 25–27, 2026), focused on practical workflows for training and deploying control policies on humanoid robots. The training is delivered by The Construct Robotics Institute and is designed for engineers and researchers interested in reinforcement learning applied to humanoid systems. During the bootcamp, pa
Open source S2
nt Learning Bootcamp DSCF1537 6240×3512 468 KB Participants will train and validate policies in simulation and deploy them on real humanoid robots (Unitree G1). The format is fully practical, with all sessions focused on implementation and experimentation. If relevant to your work, more details are available here: https://www.theconstruct.ai/humanoid-robot-reinforcement-learning-training/
Open source S4
rticipants will work through the main components of a sim-to-real pipeline: RL-based walking control using Isaac Lab and MuJoCo Whole-body control and motion imitation Teleoperation and imitation learning with Isaac Mimic Vision-Language-Action (VLA) models with Gr00t Sim-to-sim validation and deployment on real robots Humanoid Robot Reinforcement Learning Bootcamp DSCF1603 6240×3512 478 KB Humanoid Robot Reinforceme
Open source S3
Source：ROS Discourse — Community updates · discourse.openrobotics.org