AMS
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AMS is a humanoid training system by Kinetix AI that enables robots to learn agile motion and stable balance through combined real-world and simulated data.
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AMS is a humanoid training system by Kinetix AI that enables robots to learn agile motion and stable balance through combined real-world and simulated data.

DAS Dex by Genrobot.AI is a high-fidelity hand tracking glove designed for embodied AI, enabling scalable and precise data collection for humanoid robot training.


OpenDroids Data Collection Glove C1 enables precise motion capture and teleoperation, helping teams generate high-quality training data for robotic systems.


The gForcePro+ EMG armband by OYMotion captures muscle signals and motion data to translate human gestures into real-time inputs for training dexterous robotic systems and AI models.


HAL by Cyberdyne is a whole-body teleoperation exoskeleton that translates human movement into real-time humanoid robot control for training and imitation learning.


HaptX Gloves G1 deliver highly realistic tactile feedback and precise motion tracking, enabling immersive interaction and high-quality data collection for humanoid robotics.


HexaCircle Multi-Hand Controller enables one operator to control multiple robot hands simultaneously, scaling high-quality data collection for humanoid hand AI training.


OptiTrack Prime Series by OptiTrack provides high-precision optical motion capture for humanoid robotics research, enabling reliable human motion data for AI training and teleoperation.


The Perception Neuron 3 by Noitom provides full-body motion capture for robotics and AI training, enabling natural human movement to drive humanoid learning and teleoperation systems.


AgileX Robotics PIKA is a data collection platform that captures human motion demonstrations to support robotic training and embodied AI development.


Psi E1 is an anthropomorphic exoskeleton by PsiBot that captures real-world human motion data to train and improve embodied AI models.

Quantum Metagloves by MANUS deliver highly accurate finger tracking and seamless integration, enabling realistic hand motion capture for animation, VR, and robotics applications.


SenseGlove Nova 2 is a wireless haptic data glove that combines motion capture with force and touch feedback, enabling realistic interaction and high-quality training data for humanoid robotics.


Sunday AI Skill Capture Glove™ enables robots to learn manipulation tasks from human hand demonstrations through teleoperation-based data collection.


Sensobright tactile sensors enable robots to detect and respond to physical contact, improving precision, safety, and adaptive manipulation.


TWIST by Stanford University is a whole-body imitation system that enables real-time humanoid teleoperation and generates high-quality training data through natural human movement.