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In house tactile sensor prototype. Detects taps, motion, and multiple contact with force magnitudes. Built to be cheap, robust, and replaceable. Not in our demos yet, still WIP. We pair simple tactile sensing with torque transparent joints to recover rich contact without expensive sensors.

Kyber Labs

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38,930 views • 4 months ago •via X (Twitter)

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ManiFeel is a benchmark for contact-rich manipulation tasks. Force- and tactile-based tasks with occlusions and partially-observable state are going to be crucial for true general purpose robotics. Website:

ManiFeel is a benchmark for contact-rich manipulation tasks. Force- and tactile-based tasks with occlusions and partially-observable state are going to be crucial for true general purpose robotics. Website:

Chris Paxton

12,063 views • 5 months ago

Now all you need to make tactile sensors is a 3D printer, magnets, and magnetometers! [📍It’s open source!] A new tactile sensor, called e-Flesh, with a simple working principle… measure deformations in 3D printable microstructures. Since e-Flesh is 3D printable, you can make it in all shapes and sizes for applications ranging from foot fall sensing to multifingered hands. This is critical in getting touch not just on fingertips, but all around robots. eFlesh can democratize touch sensing with open-sourced❗️ Make your own: Paper:

Now all you need to make tactile sensors is a 3D printer, magnets, and magnetometers! [📍It’s open source!] A new tactile sensor, called e-Flesh, with a simple working principle… measure deformations in 3D printable microstructures. Since e-Flesh is 3D printable, you can make it in all shapes and sizes for applications ranging from foot fall sensing to multifingered hands. This is critical in getting touch not just on fingertips, but all around robots. eFlesh can democratize touch sensing with open-sourced❗️ Make your own: Paper:

Ilir Aliu

154,910 views • 6 months ago

Open-source magnetic tactile sensor for $5! 🧲 Researchers introduced a magnetic tactile sensor that's low-cost, and easy to fabricate, democratizing tactile sensing for robotics. Operating in unstructured environments like homes and offices requires robots to sense forces during physical interaction. Yet the lack of a versatile, accessible tactile sensor has led to fragmented solutions and often force-unaware, sensorless approaches. Building an eFlesh sensor requires four components: a hobbyist 3D printer, off-the-shelf magnets (less than $5), a CAD model, and a magnetometer circuit board. The sensor is 3D printed with magnets embedded in the middle layer. Based on chosen mechanical properties, magnets displace in response to contact forces, measured by a magnetometer underneath. An open-source design tool converts simple OBJ/STL files into 3D-printable STLs. This enables application-specific sensors for robot hands, grippers, quadruped feet, and more. Slip detection generalizes to unseen objects with 95% accuracy. Visual-tactile control policies improve manipulation by 40% over vision-only baselines, achieving 90% success on precise tasks like plug insertion and credit card swiping. All design files, code, trained models, and conversion tools are openly available. Project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Open-source magnetic tactile sensor for $5! 🧲 Researchers introduced a magnetic tactile sensor that's low-cost, and easy to fabricate, democratizing tactile sensing for robotics. Operating in unstructured environments like homes and offices requires robots to sense forces during physical interaction. Yet the lack of a versatile, accessible tactile sensor has led to fragmented solutions and often force-unaware, sensorless approaches. Building an eFlesh sensor requires four components: a hobbyist 3D printer, off-the-shelf magnets (less than $5), a CAD model, and a magnetometer circuit board. The sensor is 3D printed with magnets embedded in the middle layer. Based on chosen mechanical properties, magnets displace in response to contact forces, measured by a magnetometer underneath. An open-source design tool converts simple OBJ/STL files into 3D-printable STLs. This enables application-specific sensors for robot hands, grippers, quadruped feet, and more. Slip detection generalizes to unseen objects with 95% accuracy. Visual-tactile control policies improve manipulation by 40% over vision-only baselines, achieving 90% success on precise tasks like plug insertion and credit card swiping. All design files, code, trained models, and conversion tools are openly available. Project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

289,055 views • 3 months ago

Today at Meta FAIR we’re announcing three new cutting-edge developments in robotics and touch perception — and releasing a collection of artifacts to empower the community to build on this work. Details on all of this new work ➡️ 1️⃣ Meta Sparsh is the first general-purpose encoder for vision-based tactile sensing that works across many tactile sensors and many tasks. Trained on 460K+ tactile images using self-supervised learning. 2️⃣ Meta Digit 360 is a breakthrough artificial fingertip-based tactile sensor, equipped with 18+ sensing features to deliver detailed touch data with human-level precision and touch-sensing capabilities. 3️⃣ Meta Digit Plexus is a standardized platform for robotic sensor connections and interactions. It provides a hardware-software solution to integrate tactile sensors on a single robot hand and enables seamless data collection, control and analysis over a single cable. The potential impact of expanding capabilities and components like these for the open source community ranges from medical research to supply chain, manufacturing and much more. We’re excited to continue this work with the broader community.

Today at Meta FAIR we’re announcing three new cutting-edge developments in robotics and touch perception — and releasing a collection of artifacts to empower the community to build on this work. Details on all of this new work ➡️ 1️⃣ Meta Sparsh is the first general-purpose encoder for vision-based tactile sensing that works across many tactile sensors and many tasks. Trained on 460K+ tactile images using self-supervised learning. 2️⃣ Meta Digit 360 is a breakthrough artificial fingertip-based tactile sensor, equipped with 18+ sensing features to deliver detailed touch data with human-level precision and touch-sensing capabilities. 3️⃣ Meta Digit Plexus is a standardized platform for robotic sensor connections and interactions. It provides a hardware-software solution to integrate tactile sensors on a single robot hand and enables seamless data collection, control and analysis over a single cable. The potential impact of expanding capabilities and components like these for the open source community ranges from medical research to supply chain, manufacturing and much more. We’re excited to continue this work with the broader community.

AI at Meta

453,260 views • 1 year ago

Excited to share that our work NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception has been accepted to #RSS2026! Your robot — even a low-cost one — can feel external forces without torque or tactile sensors. TL;DR: NeuralActuator is a neural actuator model that jointly predicts 1️⃣torque to capture the nonlinear and time-varying current–to–torque relationship of low-cost servos, 2️⃣external contact forces (and force detection gates) for sensorless force perception, 3️⃣and motor conditions that indicate each motor’s operating regime. Here is a fast-forward video clip ⬇️ We are also covering more robots like LeRobot-S101 and Franka Panda. More details coming soon.

Excited to share that our work NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception has been accepted to #RSS2026! Your robot — even a low-cost one — can feel external forces without torque or tactile sensors. TL;DR: NeuralActuator is a neural actuator model that jointly predicts 1️⃣torque to capture the nonlinear and time-varying current–to–torque relationship of low-cost servos, 2️⃣external contact forces (and force detection gates) for sensorless force perception, 3️⃣and motor conditions that indicate each motor’s operating regime. Here is a fast-forward video clip ⬇️ We are also covering more robots like LeRobot-S101 and Franka Panda. More details coming soon.

Zhiyang (Frank) Dou

50,498 views • 3 months ago

Who can say no to a humanoid robot that can actually feel a hug? 🤖 JQ Industries just built a fabric-based electronic skin for Unitree G1 — covering the torso, hands, and feet. This is not about appearance. It’s about giving robots real tactile sensing and pressure feedback. According to the company, the system includes tactile gloves, upper-body skin, and foot sensors. That means the robot can feel contact through its hands, detect pressure across its body, and use foot feedback to adjust balance. This is the missing layer in most humanoids. Vision alone can’t handle physical interaction. Robots need touch to grip safely, react to humans, and stay stable in real-world environments. JQ says its fiber sensors can detect forces as low as 0.01N, handle up to 3500kPa, and bend below 0.1mm radius. The system can also integrate with Isaac Sim, making tactile data usable for training and deployment. Unitree G1 is already built for manipulation and control — this adds the sensing layer it lacked. JQ says it’s now working with multiple humanoid companies, with some systems already shipping at scale. This is what happens when robots stop just seeing the world — and start physically feeling it.

Who can say no to a humanoid robot that can actually feel a hug? 🤖 JQ Industries just built a fabric-based electronic skin for Unitree G1 — covering the torso, hands, and feet. This is not about appearance. It’s about giving robots real tactile sensing and pressure feedback. According to the company, the system includes tactile gloves, upper-body skin, and foot sensors. That means the robot can feel contact through its hands, detect pressure across its body, and use foot feedback to adjust balance. This is the missing layer in most humanoids. Vision alone can’t handle physical interaction. Robots need touch to grip safely, react to humans, and stay stable in real-world environments. JQ says its fiber sensors can detect forces as low as 0.01N, handle up to 3500kPa, and bend below 0.1mm radius. The system can also integrate with Isaac Sim, making tactile data usable for training and deployment. Unitree G1 is already built for manipulation and control — this adds the sensing layer it lacked. JQ says it’s now working with multiple humanoid companies, with some systems already shipping at scale. This is what happens when robots stop just seeing the world — and start physically feeling it.

RoboHub🤖

10,952 views • 4 months ago

Can we bring human-like Touch to robots🤖? Introducing our CoRL work on 3D-ViTac. Humans rely on both vision 👁️ and touch 🫳 for complex tasks. With combined visual-tactile sensing, robots can now tackle challenging tasks, like precise in-hand reorientation, fragile objects grasping. Website: #Robotics #CoRL2024 #Touch #tactile #AI #ML

Can we bring human-like Touch to robots🤖? Introducing our CoRL work on 3D-ViTac. Humans rely on both vision 👁️ and touch 🫳 for complex tasks. With combined visual-tactile sensing, robots can now tackle challenging tasks, like precise in-hand reorientation, fragile objects grasping. Website: #Robotics #CoRL2024 #Touch #tactile #AI #ML

Binghao Huang

49,544 views • 1 year ago

I was really impressed by the UMI gripper (Cheng Chi et al.), but a key limitation is that **force-related data wasn’t captured**: humans feel haptic feedback through the mechanical springs, but the robot couldn’t leverage that info, limiting the data’s value for fine-grained manipulation tasks. Led by my amazing students Yolanda Zhu and Binghao Huang, we designed a **portable visuo-tactile gripper** by integrating our dense, flexible tactile arrays with the UMI gripper to enable large-scale in-the-wild data collection. 🔗 We demonstrate **cross-modal representation learning** and **downstream policy learning** on tasks requiring in-hand state estimation (e.g., test tube reorientation) and fine-grained force sensing (e.g., pipette fluid transfer). Key takeaways: - Our flexible tactile arrays store the rich haptic information humans perceive as dense tactile signals. - Portability and robustness are key for in-the-wild data collection; our portable gripper is compact, lightweight, and durable. - Touch provides precise, robust measurements of in-hand object pose, invariant to lighting and viewpoint. - Cross-modal pretraining on large-scale in-the-wild data significantly improves policy robustness and sample efficiency (as shown many times before — and verified again here!). Also check out our previous investigations of dense, flexible tactile grids for understanding human-robot-environment interactions: - Dense tactile glove (Nature ’19): - 3D-ViTac (CoRL ’24):

I was really impressed by the UMI gripper (Cheng Chi et al.), but a key limitation is that force-related data wasn’t captured: humans feel haptic feedback through the mechanical springs, but the robot couldn’t leverage that info, limiting the data’s value for fine-grained manipulation tasks. Led by my amazing students Yolanda Zhu and Binghao Huang, we designed a portable visuo-tactile gripper by integrating our dense, flexible tactile arrays with the UMI gripper to enable large-scale in-the-wild data collection. 🔗 We demonstrate cross-modal representation learning and downstream policy learning on tasks requiring in-hand state estimation (e.g., test tube reorientation) and fine-grained force sensing (e.g., pipette fluid transfer). Key takeaways: - Our flexible tactile arrays store the rich haptic information humans perceive as dense tactile signals. - Portability and robustness are key for in-the-wild data collection; our portable gripper is compact, lightweight, and durable. - Touch provides precise, robust measurements of in-hand object pose, invariant to lighting and viewpoint. - Cross-modal pretraining on large-scale in-the-wild data significantly improves policy robustness and sample efficiency (as shown many times before — and verified again here!). Also check out our previous investigations of dense, flexible tactile grids for understanding human-robot-environment interactions: - Dense tactile glove (Nature ’19): - 3D-ViTac (CoRL ’24):

Yunzhu Li

13,188 views • 1 year ago

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n

Zhi (Leo) Wang

50,541 views • 1 month ago

Force-sensing fingers! 🧤 Stanford researchers just released UMI-FT, a handheld data collection platform that puts compact six-axis force/torque sensors on each finger, enabling finger-level wrench measurements alongside RGB, depth, and pose data. Many manipulation tasks require careful force modulation: too little force and the task fails, too much and you cause damage. But commercial force/torque sensors are expensive, bulky, and fragile, which has limited large-scale force-aware policy learning. UMI-FT changes the economics. The platform uses an iPhone for RGB vision, ultrawide RGB, depth, and pose via ARKit, with each finger sensorized using a CoinFT sensor to capture per-finger wrench information during manipulation. This multimodal data trains an adaptive compliance policy that predicts position targets, grasp force, and stiffness for execution on standard compliance controllers. The learned policy runs slowest and generates reference targets, while model-based compliance and force controllers provide delicate 6D compliance control and real-time force modulation. They tested on three contact-rich, force-sensitive tasks: whiteboard wiping (locate eraser, grasp, wipe until clean), skewering zucchini (grasp slice firmly, push onto stick until punctured), and lightbulb insertion (grasp bulb, align bayonet pin with socket slit, insert while overcoming spring force, rotate to light up). The results are clear. Policies without compliance struggle to modulate contact force and trigger safety faults from excessive force. Policies without force sensing fail to grasp unseen objects or resist reaction forces, causing slippage. Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Force-sensing fingers! 🧤 Stanford researchers just released UMI-FT, a handheld data collection platform that puts compact six-axis force/torque sensors on each finger, enabling finger-level wrench measurements alongside RGB, depth, and pose data. Many manipulation tasks require careful force modulation: too little force and the task fails, too much and you cause damage. But commercial force/torque sensors are expensive, bulky, and fragile, which has limited large-scale force-aware policy learning. UMI-FT changes the economics. The platform uses an iPhone for RGB vision, ultrawide RGB, depth, and pose via ARKit, with each finger sensorized using a CoinFT sensor to capture per-finger wrench information during manipulation. This multimodal data trains an adaptive compliance policy that predicts position targets, grasp force, and stiffness for execution on standard compliance controllers. The learned policy runs slowest and generates reference targets, while model-based compliance and force controllers provide delicate 6D compliance control and real-time force modulation. They tested on three contact-rich, force-sensitive tasks: whiteboard wiping (locate eraser, grasp, wipe until clean), skewering zucchini (grasp slice firmly, push onto stick until punctured), and lightbulb insertion (grasp bulb, align bayonet pin with socket slit, insert while overcoming spring force, rotate to light up). The results are clear. Policies without compliance struggle to modulate contact force and trigger safety faults from excessive force. Policies without force sensing fail to grasp unseen objects or resist reaction forces, causing slippage. Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

12,822 views • 6 months ago

Open-source dexterous hands with fingertip sensors! 🪬 ORCA Dexterity just released three dexterous hand models. Their mission: is to democratize robotic hand dexterity. They're sharing progress on exceptional, low-cost hardware and a software layer from low-level control to robotic hand learning. This is the open-source approach to dexterous manipulation. It has 83 taxels per finger with 0.1 N force detection which pretty is impressive for an open-source design. Tactile sensing is critical for dexterous manipulation, knowing contact forces enables gentle grasping, slip detection, and force-controlled assembly. Also 700g weight for the lite version makes it practical for mounting on robot arms without exceeding payload limits. Lower weight means faster movements and lower torque requirements. Open hardware accelerates robotics by letting researchers and builders modify designs for their specific needs without starting from scratch! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Open-source dexterous hands with fingertip sensors! 🪬 ORCA Dexterity just released three dexterous hand models. Their mission: is to democratize robotic hand dexterity. They're sharing progress on exceptional, low-cost hardware and a software layer from low-level control to robotic hand learning. This is the open-source approach to dexterous manipulation. It has 83 taxels per finger with 0.1 N force detection which pretty is impressive for an open-source design. Tactile sensing is critical for dexterous manipulation, knowing contact forces enables gentle grasping, slip detection, and force-controlled assembly. Also 700g weight for the lite version makes it practical for mounting on robot arms without exceeding payload limits. Lower weight means faster movements and lower torque requirements. Open hardware accelerates robotics by letting researchers and builders modify designs for their specific needs without starting from scratch! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

38,094 views • 4 months ago

Touch alone isn’t enough. 🖐️ For robotics, tactile intelligence truly levels up when touch gains spatial meaning. At #ICRA2026, we dove into the core concept behind SaTA: Spatially-anchored Tactile Awareness for robust, dexterous manipulation. Read it here: The challenge is fundamental: a robot shouldn’t just register a touch, it needs to understand exactly where that contact occurs relative to its fingers, joints, and overall hand structure. This is the missing link that turns raw data into precise, real-time adjustments during manipulation. Why does this matter? Because the most complex part of any manipulation task happens when vision is at its least reliable, that final millimeter before insertion, sliding, gripping, or fine-tuning. At Sharpa, this is exactly why we’re building tactile hands and tactile AI in tandem. 🚀 #Sharpa #Robotics #EmbodiedAI #TactileIntelligence #ICRA2026 #DexterousManipulation 📷

Touch alone isn’t enough. 🖐️ For robotics, tactile intelligence truly levels up when touch gains spatial meaning. At #ICRA2026, we dove into the core concept behind SaTA: Spatially-anchored Tactile Awareness for robust, dexterous manipulation. Read it here: The challenge is fundamental: a robot shouldn’t just register a touch, it needs to understand exactly where that contact occurs relative to its fingers, joints, and overall hand structure. This is the missing link that turns raw data into precise, real-time adjustments during manipulation. Why does this matter? Because the most complex part of any manipulation task happens when vision is at its least reliable, that final millimeter before insertion, sliding, gripping, or fine-tuning. At Sharpa, this is exactly why we’re building tactile hands and tactile AI in tandem. 🚀 #Sharpa #Robotics #EmbodiedAI #TactileIntelligence #ICRA2026 #DexterousManipulation 📷

Sharpa

15,168 views • 2 months ago

No one could turn down a humanoid robot with human-like tactile sensitivity. JQ Industries equipped the Unitree G1 humanoid robot with a fabric-based electronic skin (piezoresistive flexible tactile sensors). A light touch can convert pressure, deformation, and slip into electrical signals, which are then processed by AI for real-time closed-loop control.(Integrates NVIDIA Isaac Sim) With this skin,humanoid robots start to behave more naturally: Touch sensing is no longer limited to dexterous hands,the entire body can feel, allowing the robot to stop or adjust posture instantly during collisions. It can also detect hugs, taps on the shoulder, or gentle touches, and respond in a softer, more human-like way. This matters especially in elder care and medical rehabilitation. A humanoid robot could gently help someone stand up, or control force precisely during assisted massage without harming the skin. Rigid mechanical systems deliver superhuman physical strength, while flexible sensing systems enable nuanced emotions. Electronic skin bridges high intelligence and high emotional intelligence.

No one could turn down a humanoid robot with human-like tactile sensitivity. JQ Industries equipped the Unitree G1 humanoid robot with a fabric-based electronic skin (piezoresistive flexible tactile sensors). A light touch can convert pressure, deformation, and slip into electrical signals, which are then processed by AI for real-time closed-loop control.(Integrates NVIDIA Isaac Sim) With this skin,humanoid robots start to behave more naturally: Touch sensing is no longer limited to dexterous hands,the entire body can feel, allowing the robot to stop or adjust posture instantly during collisions. It can also detect hugs, taps on the shoulder, or gentle touches, and respond in a softer, more human-like way. This matters especially in elder care and medical rehabilitation. A humanoid robot could gently help someone stand up, or control force precisely during assisted massage without harming the skin. Rigid mechanical systems deliver superhuman physical strength, while flexible sensing systems enable nuanced emotions. Electronic skin bridges high intelligence and high emotional intelligence.

CyberRobo

22,118 views • 4 months ago

Chris Finch on officiating: "The league's in a place right now where you draw the contact, spill away, and get rewarded. Guys who try to play through contact ... stay with the drive, they tend not to be rewarded ... Maybe we ought to start flopping too."

Chris Finch on officiating: "The league's in a place right now where you draw the contact, spill away, and get rewarded. Guys who try to play through contact ... stay with the drive, they tend not to be rewarded ... Maybe we ought to start flopping too."

Underdog NBA

712,329 views • 3 months ago

Researchers from RAI Institute present Diffuse-CLoC, a new control policy that fuses kinematic motion diffusion models with physics-based control to produce motions that are both physically realistic and precisely controllable. This breakthrough moves us closer to developing generalist policies that enable humanoid robots to perform diverse tasks, including dynamic locomotion and contact-rich manipulation, in a natural-looking and robust way. Learn more at

Researchers from RAI Institute present Diffuse-CLoC, a new control policy that fuses kinematic motion diffusion models with physics-based control to produce motions that are both physically realistic and precisely controllable. This breakthrough moves us closer to developing generalist policies that enable humanoid robots to perform diverse tasks, including dynamic locomotion and contact-rich manipulation, in a natural-looking and robust way. Learn more at

RAI Institute

13,536 views • 11 months ago

Touch: A Game-Changer in Dexterity for Robots You can’t be responsive to the world if you can’t feel it. That’s true for people—and it's just as true for robots. We’re zeroed in on a practical, yet innovative, approach to creating general purpose robots designed to perform physical work. And that means hands, powered not just by vision, but by touch. Vision alone falls short. There are many instances where our vision is obstructed while performing work tasks–like grabbing items out of a bin–you lose line of sight. You need tactile intelligence—texture, pressure, contact—with real-time feedback to move faster, smarter, and with confidence. Watch a full explainer video on Sanctuary AI’s latest touch sensors on our blog: #Robotics #AI #HumanoidRobots #Dexterity #TactileSensing #SanctuaryAI

Touch: A Game-Changer in Dexterity for Robots You can’t be responsive to the world if you can’t feel it. That’s true for people—and it's just as true for robots. We’re zeroed in on a practical, yet innovative, approach to creating general purpose robots designed to perform physical work. And that means hands, powered not just by vision, but by touch. Vision alone falls short. There are many instances where our vision is obstructed while performing work tasks–like grabbing items out of a bin–you lose line of sight. You need tactile intelligence—texture, pressure, contact—with real-time feedback to move faster, smarter, and with confidence. Watch a full explainer video on Sanctuary AI’s latest touch sensors on our blog: #Robotics #AI #HumanoidRobots #Dexterity #TactileSensing #SanctuaryAI

Sanctuary AI

53,269 views • 1 year ago

A dexterous hand capable of operating an iPhone Impressive, with nimble fingertip control. INSPIRE ROBOTS from Beijing has released a new dexterous hand featuring tactile and force sensing, and equipped with a motion library, making it ready to use right out of the box. Especially noteworthy is the modular finger design, allowing users to easily replace a damaged finger. With 13 degrees of freedom and a single-hand load capacity of 30kg, it can be used in general applications such as factory component handling, precision assembly, and warehouse logistics sorting. Notably, this company has already sold over 10,000 of these dexterous hands.

A dexterous hand capable of operating an iPhone Impressive, with nimble fingertip control. INSPIRE ROBOTS from Beijing has released a new dexterous hand featuring tactile and force sensing, and equipped with a motion library, making it ready to use right out of the box. Especially noteworthy is the modular finger design, allowing users to easily replace a damaged finger. With 13 degrees of freedom and a single-hand load capacity of 30kg, it can be used in general applications such as factory component handling, precision assembly, and warehouse logistics sorting. Notably, this company has already sold over 10,000 of these dexterous hands.

CyberRobo

14,196 views • 7 months ago

❗️Day 19 of the Ukrainian oil blockade. Our experts are still denied access to the Friendship pipeline while Brussels still refuses to face reality: Europe cannot overcome the energy crisis without cheap Russian oil, yet their sanctions remain in place. In Hungary we protect our families, farmers and businesses with protected prices and secure supplies. Tomorrow we march for peace. It’s time to push back against Ukrainian blackmail: Volodymyr Zelenskyy / Володимир Зеленський will not give orders here!

❗️Day 19 of the Ukrainian oil blockade. Our experts are still denied access to the Friendship pipeline while Brussels still refuses to face reality: Europe cannot overcome the energy crisis without cheap Russian oil, yet their sanctions remain in place. In Hungary we protect our families, farmers and businesses with protected prices and secure supplies. Tomorrow we march for peace. It’s time to push back against Ukrainian blackmail: Volodymyr Zelenskyy / Володимир Зеленський will not give orders here!

Orbán Viktor

453,710 views • 4 months ago

🗒️WIP Wednesday #25🗒️ - PROTOTYPE PLAYTHROUGH - PART TWO Welcome to another 'Work In Progress Wednesday'. To follow on from last weeks 'PART ONE' here's the 'PART TWO' of our prototype playthrough, which focusses on.......foraging and crafting! 🫳 🌱 🫴 For the next few weeks we will be showing you snippets of the full prototype playthrough & from next week we will be getting this into the hands of our ⛏️ PIONEERS & those who made the 🐦 EARLY LIST to play, build and test with us. Want in? Keep an eye on our twitter and stay dedicated. Remember, this is an early prototype so everything's super rough still. 💚

🗒️WIP Wednesday #25🗒️ - PROTOTYPE PLAYTHROUGH - PART TWO Welcome to another 'Work In Progress Wednesday'. To follow on from last weeks 'PART ONE' here's the 'PART TWO' of our prototype playthrough, which focusses on.......foraging and crafting! 🫳 🌱 🫴 For the next few weeks we will be showing you snippets of the full prototype playthrough & from next week we will be getting this into the hands of our ⛏️ PIONEERS & those who made the 🐦 EARLY LIST to play, build and test with us. Want in? Keep an eye on our twitter and stay dedicated. Remember, this is an early prototype so everything's super rough still. 💚

Youmio

42,277 views • 3 years ago