Precision data gloves that bring human dexterity to robotics and motion capture.
Eindhoven, The Netherlands
Joined June 2014
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MANUS Core 3.2 is here.
This release brings Linux ARM64 support, more accurate and consistent pinch tracking across a wide range of hand sizes, a new Python SDK, and haptic feedback support in NVIDIA Isaac Teleop.
Download MANUS Core 3.2:
docs.manus-meta.com/3.2.1/Re…
Read the release notes:
docs.manus-meta.com/3.2.0/Re…
MANUS retweeted
mimic demonstrates real-time teleoperation of its dexterous robotic hand using MANUS gloves, live from NVIDIA GTC in Berlin.
Video Credit: @ManusMeta
#engineering #technology
Live from NVIDIA GTC in Berlin: @mimicrobotics demonstrates real-time teleoperation of its dexterous robotic hand using @ManusMeta gloves. Precise hand input, fine manipulation, live on the show floor.
#NVIDIAGTC #GTCBerlin #GTC2026 #robotics #PhysicalAI @NVIDIAGTC @NVIDIARobotics @nvidia
We’re in Berlin for NVIDIA GTC! 🇩🇪
Fantastic keynote from Jensen Huang, and great to catch up with so many familiar faces from the robotics community!
If you’re working on dexterous manipulation, robot learning, or scaling human hand data collection, we’d love to connect.
See you around at #GTCBerlin! 🤖
Human hand motion. Allegro Hand control. Powered by MANUS.
Wonik Robotics demonstrated real-time teleoperation of its Allegro Hand V6, using MANUS Metagloves Pro Haptic.
Contact data from the Allegro Hand’s tactile sensors can be mapped to vibration cues on Metagloves Pro Haptic, improving contact awareness during teleoperation.
@Honda showcases dexterous teleoperation of its Avatar robot with MANUS data gloves.
Equipped with @ManusMeta data gloves and a headset, the operator controls both robotic hands to perform a tool-based screw-tightening task.
MANUS gloves capture precise finger movements in real time, providing high-fidelity hand-motion data for teleoperation. Combined with Honda’s robotic control and AI-assisted system, this enables coordinated dexterous manipulation.
#MANUS #Honda #Teleoperation #Robotics #PhysicalAI
EgoExplorer from Shanghai AI Lab: 100 hours of real-world tasks with synced egocentric video, full-body motion and hand data.
The EgoExplorer research team described MANUS data gloves as “the backbone of our hand stream.”
By capturing walking, posture changes, grasping and object manipulation as one continuous whole, EgoExplorer gives humanoid retargeting, whole-body control and embodied AI research richer human demonstrations to learn from.
📄github.com/InternRobotics/Eg…
Congratulations to @Yunsong_Zhou and the team. We’re proud to see MANUS gloves be part of this work.
BrainCo is using MANUS data gloves to test its vector-based retargeting algorithm for the Revo 3 dexterous hand.
MANUS gloves provide real-time joint angles and fingertip positions, enabling precise mapping of human hand movements to robotic hands.
Combined with @BrainCo_Tech's optimized control pipeline, the system delivers natural motion mapping, smooth hand tracking, and low-latency teleoperation, supporting the collection of high-quality human demonstrations for imitation learning.
#MANUS #Teleoperation #ImitationLearning #PhysicalAI
MANUS retweeted
Honda showcased their Avatar Robot at CEATEC 2026, a remotely operated system designed to act as a second life so you can perform tasks from anywhere without being physically on-site.
It combines a multi-fingered hand with human-like dexterity and strength plus an AI support system that assists the operator in real time.
They're targeting applications such as healthcare, facility maintenance, disaster response, and space development.
The spirit of Asimo is still alive at Honda.
Hands up if you had fun at the MANUS BBQ! 🙌
We teach humanoid robots to move like us, and our team is growing fast.
If you’ve been waiting for the right moment to join, this is it.
👉 See our open roles: manus-meta.com/careers
Boom💥
Teleoperating two Ability Hands with @ManusMeta gloves on @AgilexRobotics Nero arms 🦾🦾
Hand and arm data streams into a full 3D sim synced to a depth camera, all built with @claudeai. Real to sim data that can train models to run these tasks autonomously.
Boom 💥
MANUS Metaglove Pro Haptic captures the operator’s finger movements in real time through 25-DoF hand tracking, mapping the tracking data to the 22-DoF, fully direct-drive @Xynova Prima 1 dexterous hand for continuous, precise robotic motion.
From data acquisition to robotic execution, MANUS combines high-precision tracking with low-latency data output to support smooth, stable, real-time teleoperation with reliable motion data and haptic feedback.
MANUS retweeted
Meet your 10 chosen Groundbreaking Technology finalists for the Humanoid Robotics Industry Awards 2026!
🔸@DobotRobotics - DOBOT LUMO
🔸@JakaRobotics - JAKA Kargo
🔸@LimX_Dynamics – LimX Luna
🔸@ManusMeta - Metagloves Pro Haptic
🔸Perceptyne - PR-OMNI
🔸PNDbotics – ADAM
🔸ROBROS- IGRIS-C
🔸@Sarco_Dynamics - ARTUS Lite
🔸@Tesla_Optimus - Optimus
🔸@XsenHS - Xsens Link Suit
Your nominations put these ten on the shortlist. Now your votes decide who takes the title!
Vote here: humanoidroboticstechnology.c…
From everyone at Humanoid Robotics Technology and our partner for this year's awards, Novanta Inc., a massive congratulations to all ten finalists👏
#humanoidroboticsindustryawards2026 #humanoidrobotics #humanoids
In a recent study from @ADI_News, “Touch2Trace,” a robotic hand was trained to feed cables through its fingers using tactile sensing and joint-state feedback, without visual input. By combining a pretrained tactile encoder with imitation learning, the policy demonstrated zero-shot transfer to unseen cables and routing conditions.
To collect demonstrations, operators used MANUS Metagloves Pro to track finger joint angles and teleoperate a @Tesollo_Inc DG-5F hand through a custom retargeting pipeline. Robot joint commands, joint states and tactile data from sensors on the robot’s fingertips were recorded together for training.
Read more: grmmtt.github.io/corl26-touc…
We made the finals!🏆MANUS Metagloves Pro Haptic is a finalist for Groundbreaking Technology at the Humanoid Robotics Industry Awards 2026.
We’d love your support. Can we count on your vote? 👇
humanoidroboticstechnology.c…
Thanks for sharing what we’re building at MANUS.
Your hands are becoming a robot’s input device. 🤖🖐️
MANUS Core 3.2 brings several updates for robotic hand tracking, including native Linux ARM64 support, more precise pinch tracking across different hand sizes, a new Python SDK, and haptic feedback integration with NVIDIA Isaac Teleop.
That means developers can bring high-fidelity hand motion data closer to the robot itself an important piece of the puzzle for teleoperation, robot learning and dexterous manipulation.
The interesting question is: How close are we to controlling robots as naturally as we control our own hands?
🏢 Company: @ManusMeta
⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.
#Robotics #RobotHand #DexterousRobotics #Teleoperation #PhysicalAI #AI #RoboticsTechnology #NVIDIA #IsaacTeleop #MANUS
MANUS retweeted
Your hands are becoming a robot’s input device. 🤖🖐️
MANUS Core 3.2 brings several updates for robotic hand tracking, including native Linux ARM64 support, more precise pinch tracking across different hand sizes, a new Python SDK, and haptic feedback integration with NVIDIA Isaac Teleop.
That means developers can bring high-fidelity hand motion data closer to the robot itself an important piece of the puzzle for teleoperation, robot learning and dexterous manipulation.
The interesting question is: How close are we to controlling robots as naturally as we control our own hands?
🏢 Company: @ManusMeta
⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.
#Robotics #RobotHand #DexterousRobotics #Teleoperation #PhysicalAI #AI #RoboticsTechnology #NVIDIA #IsaacTeleop #MANUS
MANUS retweeted
.@Xynovaofficial_ is one of the top rising players in China’s dexterous hand and humanoid robot components space, based in Hangzhou
• They develop not only the hands but also all core components (linear actuators, motors, etc) and algorithms fully in-house
• They use a hybrid drive system, combining tendon-driven and direct-drive methods
• One of the most exciting features is wrist control and finger abduction/adduction, delivering much more natural hand and arm dexterity
• They prevent the hand from overheating by placing one of the actuators in the arm (below the palm)
• Hands are equipped with tactile sensors and lidars, with 23 DoF (human hands have ~27 DoF)
The overall design is deeply inspired by real human hand and arm muscle movements, impressive biomimicry approach
@TheHumanoidHub and I interviewed their tech lead so stay tuned for more technical details!