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Pollen Robotics, a Hugging Face subsidiary, has open-sourced Amazing Hand, a 3D-printable, four-finger robotic hand with eight degrees of freedom (DoF). Weighing 400g and costing less than $250 - it is designed for Reachy2’s wrist but adaptable to other robots.

The Humanoid Hub

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AR and Robotics is such an amazing combination The video doesn’t do it justice but interacting natively in 3D space is intuitive and feels natural This is @Spectacles driving a Reachy Mini from Hugging Face and Pollen Robotics Thanks again to SensAI Hackademy 🙂

AR and Robotics is such an amazing combination The video doesn’t do it justice but interacting natively in 3D space is intuitive and feels natural This is @Spectacles driving a Reachy Mini from Hugging Face and Pollen Robotics Thanks again to SensAI Hackademy 🙂

Johannes Tscharn

54,386 Aufrufe • vor 6 Monaten

Super excited to visit WUJI TECH who's pushing the frontier with their advanced dexterous robotic hand Most traditional robotic hands still rely on tendons/cables, but Wuji Hand uses direct-drive actuators embedded right in the fingers with worm gears. This solves the usual tendon problems by delivering smoother, more precise, and reliable motion with way less sim-to-real gap It also has high dexterity with 20 active degrees of freedom and the weight/size feel almost exactly like an adult human hand Got to test the newly launched Wuji Hand 2 today and was super fascinated! (watch how I handle the hand in the first video😂)

Super excited to visit WUJI TECH who's pushing the frontier with their advanced dexterous robotic hand Most traditional robotic hands still rely on tendons/cables, but Wuji Hand uses direct-drive actuators embedded right in the fingers with worm gears. This solves the usual tendon problems by delivering smoother, more precise, and reliable motion with way less sim-to-real gap It also has high dexterity with 20 active degrees of freedom and the weight/size feel almost exactly like an adult human hand Got to test the newly launched Wuji Hand 2 today and was super fascinated! (watch how I handle the hand in the first video😂)

Lena

46,924 Aufrufe • vor 27 Tagen

Korean robotics leader ROBOTIS has unveiled the 'AI Sapiens' humanoid, a direct challenge to Unitree’s G1 and R1 models. - 4'3" (130 cm) tall and weighing 34 kg. - Features 23 DOF, powered by the brand-new Dynamixel-Q actuators. The robot is a fully open-source hardware system designed to serve as a reliable hardware platform for advanced Physical AI research. AI Sapiens is slated for an H1 2026 launch, with a price point expected in the mid-to-low 10 million KRW range (~$7,000 – $8,700 USD).

The Humanoid Hub

95,469 Aufrufe • vor 2 Monaten

Imagine having a ping pong robot! 🏓 Researchers and developers building physical AI: meet Reachy 2 from Pollen Robotics, an open-source, humanoid robot for real-world experimentation. It’s a bimanual mobile manipulator: each 7-DOF arm mimics human proportions and can lift up to 3 kg, giving dexterity for object handling. It can be controlled with Python and ROS2 Humble, or go straight into VR teleoperation, use a headset to move Reachy’s arms, hands, and head, and see through its cameras as if you’re in the robot’s own body. Want it to move around? A mobile base with three omnidirectional wheels, rich sensors, and LiDAR lets Reachy 2 navigate and explore its surroundings smoothly. 🗺️ Under the hood, it’s powered by a CPU system that’s ready for machine learning, perfect for loading AI frameworks and testing new models from Hugging Face directly on the robot. Keep making robots more, and more accessible Pollen team! ... and keep making more open source models to make robots more mainstream clem 🤗!

Imagine having a ping pong robot! 🏓 Researchers and developers building physical AI: meet Reachy 2 from Pollen Robotics, an open-source, humanoid robot for real-world experimentation. It’s a bimanual mobile manipulator: each 7-DOF arm mimics human proportions and can lift up to 3 kg, giving dexterity for object handling. It can be controlled with Python and ROS2 Humble, or go straight into VR teleoperation, use a headset to move Reachy’s arms, hands, and head, and see through its cameras as if you’re in the robot’s own body. Want it to move around? A mobile base with three omnidirectional wheels, rich sensors, and LiDAR lets Reachy 2 navigate and explore its surroundings smoothly. 🗺️ Under the hood, it’s powered by a CPU system that’s ready for machine learning, perfect for loading AI frameworks and testing new models from Hugging Face directly on the robot. Keep making robots more, and more accessible Pollen team! ... and keep making more open source models to make robots more mainstream clem 🤗!

Lukas Ziegler

37,221 Aufrufe • vor 10 Monaten

.Xynova 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 The Humanoid Hub and I interviewed their tech lead so stay tuned for more technical details!

.Xynova 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 The Humanoid Hub and I interviewed their tech lead so stay tuned for more technical details!

Lena

57,094 Aufrufe • vor 20 Tagen

Another magical encounter with an extraordinary bird today. This beautiful little goldcrest came to say hello. It’s Europe’s smallest bird weighing a little less than a 20p coin and yet each year it manages to cross the North Sea. It may be small but it has the heart of a lion!

Another magical encounter with an extraordinary bird today. This beautiful little goldcrest came to say hello. It’s Europe’s smallest bird weighing a little less than a 20p coin and yet each year it manages to cross the North Sea. It may be small but it has the heart of a lion!

Gwydir Castle

37,393 Aufrufe • vor 3 Monaten

Genesis AI just unveiled Eno. It's humanoid robot that challenges everything the industry assumed about what robots should look like. Forbes just called it 'the iPhone moment for humanoid robots'. No head. No face. No exposed motors or cables. 22 degrees of freedom per hand with different finger lengths (like actual human hands). Back-drivable for safety. Onboard cameras and tactile sensors. In demos: bundling wires with tape (genuinely hard, tape is sticky and unpredictable), performing lab automation with millimeter precision on unmodified equipment. Optional chest screen shows the robot's reasoning before it acts, a visual window into its mind to build trust. Powered by Genesis AI GENE foundation model. Payload 3-5kg per arm, 4-6 hours battery. Industrial deployments late 2026, homes much later. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Genesis AI just unveiled Eno. It's humanoid robot that challenges everything the industry assumed about what robots should look like. Forbes just called it 'the iPhone moment for humanoid robots'. No head. No face. No exposed motors or cables. 22 degrees of freedom per hand with different finger lengths (like actual human hands). Back-drivable for safety. Onboard cameras and tactile sensors. In demos: bundling wires with tape (genuinely hard, tape is sticky and unpredictable), performing lab automation with millimeter precision on unmodified equipment. Optional chest screen shows the robot's reasoning before it acts, a visual window into its mind to build trust. Powered by Genesis AI GENE foundation model. Payload 3-5kg per arm, 4-6 hours battery. Industrial deployments late 2026, homes much later. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

29,127 Aufrufe • vor 28 Tagen

Elon Musk has repeatedly highlighted the hand (and forearm) as one of the toughest engineering challenges for Tesla’s Optimus Robot. A new Patent (for presumably Optimus 3) shows Tesla is using human anatomy to recreate a tendon-driven robotic hand and forearm assembly that closely mimics a human system. Basically, Tesla is replacing human muscles with actuators and tendons with cables to replicate human dexterity. The Tesla Engineering team is on another level. Optimus Gen 3 reveal is going to be incredible.

Elon Musk has repeatedly highlighted the hand (and forearm) as one of the toughest engineering challenges for Tesla’s Optimus Robot. A new Patent (for presumably Optimus 3) shows Tesla is using human anatomy to recreate a tendon-driven robotic hand and forearm assembly that closely mimics a human system. Basically, Tesla is replacing human muscles with actuators and tendons with cables to replicate human dexterity. The Tesla Engineering team is on another level. Optimus Gen 3 reveal is going to be incredible.

Nic Cruz Patane

93,272 Aufrufe • vor 2 Monaten

🚨 BREAKING: NVIDIA just announced the Isaac GR00T Reference Humanoid Robot. The first fully open humanoid robot reference design built on Jetson Thor, and it's going straight to the world's top research institutions. This is Jensen Huang's bet on open physical AI infrastructure. The hardware stack is serious: → Unitree H2 Plus chassis, 6 feet tall, 150 pounds, 31 degrees of freedom → Sharpa Wave tactile five-finger hands, 22 degrees of freedom, bringing total to 75 across the full body → NVIDIA Jetson AGX Thor onboard compute, 2,070 FP4 teraflops of AI performance, 128GB unified memory → Multi-view sensing, stereo head camera, wrist cameras, IMU Alongside this announcement, Unitree also introduced the H2 Plus as a standalone product, a frontier humanoid combining Unitree's own body, Sharpa's five-finger hands and NVIDIA Robotics Jetson Thor compute into one fully integrated research platform. The full Isaac GR00T software stack ships with it, teleoperation for data capture, open foundation models, Isaac Sim for training, Isaac Lab for evaluation, and accelerated ROS middleware for deployment. The complete loop from data to real-world robot in one unified platform. ETH Zürich, Stanford Robotics Center, UC San Diego and Ai2 are already on board as launch research partners. NVIDIA Robotics did to AI what it's now doing to robotics, build the platform, open the ecosystem, let the world build on top of it. Whoever owns the infrastructure layer wins. NVIDIA knows this better than anyone. 👀 Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

🚨 BREAKING: NVIDIA just announced the Isaac GR00T Reference Humanoid Robot. The first fully open humanoid robot reference design built on Jetson Thor, and it's going straight to the world's top research institutions. This is Jensen Huang's bet on open physical AI infrastructure. The hardware stack is serious: → Unitree H2 Plus chassis, 6 feet tall, 150 pounds, 31 degrees of freedom → Sharpa Wave tactile five-finger hands, 22 degrees of freedom, bringing total to 75 across the full body → NVIDIA Jetson AGX Thor onboard compute, 2,070 FP4 teraflops of AI performance, 128GB unified memory → Multi-view sensing, stereo head camera, wrist cameras, IMU Alongside this announcement, Unitree also introduced the H2 Plus as a standalone product, a frontier humanoid combining Unitree's own body, Sharpa's five-finger hands and NVIDIA Robotics Jetson Thor compute into one fully integrated research platform. The full Isaac GR00T software stack ships with it, teleoperation for data capture, open foundation models, Isaac Sim for training, Isaac Lab for evaluation, and accelerated ROS middleware for deployment. The complete loop from data to real-world robot in one unified platform. ETH Zürich, Stanford Robotics Center, UC San Diego and Ai2 are already on board as launch research partners. NVIDIA Robotics did to AI what it's now doing to robotics, build the platform, open the ecosystem, let the world build on top of it. Whoever owns the infrastructure layer wins. NVIDIA knows this better than anyone. 👀 Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

15,928 Aufrufe • vor 1 Monat

🤖 Robotic hands are evolving faster than we realize — and they’re learning to master our world. I find this both fascinating and a little unsettling. At first glance, these robotic hands still look awkward - stiff fingers, clumsy motion. But behind the scenes, every iteration brings: ➡️ Tighter sensors ➡️ Smarter control loops ➡️ Better training on human-designed objects Week by week, they move closer to something astonishing — not imitation, but mastery. They’re learning to grip, twist, and adapt to tools made for our anatomy. And once they reach human-level dexterity, they won’t stop there. They’ll surpass it — steadier than surgeons, faster than assembly lines, tireless and precise. This is more than robotics. It’s the moment machines stop mimicking us… and start outperforming us. How do we redefine “human skill” in a world where robots master it too? #AI #Robotics #Innovation #Technology #Automation #FutureOfWork #Engineering

🤖 Robotic hands are evolving faster than we realize — and they’re learning to master our world. I find this both fascinating and a little unsettling. At first glance, these robotic hands still look awkward - stiff fingers, clumsy motion. But behind the scenes, every iteration brings: ➡️ Tighter sensors ➡️ Smarter control loops ➡️ Better training on human-designed objects Week by week, they move closer to something astonishing — not imitation, but mastery. They’re learning to grip, twist, and adapt to tools made for our anatomy. And once they reach human-level dexterity, they won’t stop there. They’ll surpass it — steadier than surgeons, faster than assembly lines, tireless and precise. This is more than robotics. It’s the moment machines stop mimicking us… and start outperforming us. How do we redefine “human skill” in a world where robots master it too? #AI #Robotics #Innovation #Technology #Automation #FutureOfWork #Engineering

Pascal Bornet

97,867 Aufrufe • vor 6 Monaten

been experimenting with this for a few hours, lots of different ideas for how to improve it but here you can rly see how hard it is to move, the only thing i can do is wiggle and flap my hand 😵‍💫

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been experimenting with this for a few hours, lots of different ideas for how to improve it but here you can rly see how hard it is to move, the only thing i can do is wiggle and flap my hand 😵‍💫

husk 🖤

66,767 Aufrufe • vor 1 Jahr

Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.

Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.

Pierre-Alexandre Balland

185,895 Aufrufe • vor 6 Monaten

We’ve seen humanoid robots walk around for a while, but when will they actually help with useful tasks in daily life? The challenge here is the diversity and complexity of real-world scenes. Our new work tackles this problem via 3D visuomotor policy learning. Using data from only 1 scene, our Improved 3D Diffusion Policy (iDP3) enables a full-sized humanoid robot to autonomously pick&place objects, pour water, and wipe tables, in the wild open world. (and all these skills are useful, right?) Web: Fully open-sourced code:

We’ve seen humanoid robots walk around for a while, but when will they actually help with useful tasks in daily life? The challenge here is the diversity and complexity of real-world scenes. Our new work tackles this problem via 3D visuomotor policy learning. Using data from only 1 scene, our Improved 3D Diffusion Policy (iDP3) enables a full-sized humanoid robot to autonomously pick&place objects, pour water, and wipe tables, in the wild open world. (and all these skills are useful, right?) Web: Fully open-sourced code:

Yanjie Ze

75,248 Aufrufe • vor 1 Jahr

Owl_rz yeah it super was for the PS1. A 3D stealth game released before MGS1 and plays better than it with two protagonists having their own moveset. Levels were open and you could use a grappling hook to take advantage of rooftops. Non-linear open levels 100% is immersive to this day

Owl_rz yeah it super was for the PS1. A 3D stealth game released before MGS1 and plays better than it with two protagonists having their own moveset. Levels were open and you could use a grappling hook to take advantage of rooftops. Non-linear open levels 100% is immersive to this day

Dream's Longest Day

14,491 Aufrufe • vor 7 Monaten

🌀 #Live3D #Live2D #Live2DWIP 🌀 Today, I’d like to share two of the three methods I use to create joint twisting in my Live2D-based 2D Pseudo-3D concept. On the right is the Glue Joint： The basic idea is to use Glue to connect two pseudo-3D ArtMeshes. By taking advantage of Glue’s weight settings, it can create an effect similar to a 3D joint. Once the weights are set up, it can move very freely with a relatively low amount of work. However, it also shares the same weakness as 3D joints: when rotated at large angles, it can produce unpleasant twisting and distortion. On the left is the Hand-Bent Joint： The basic idea is to add bending Keyforms directly to a Warp Deformer, then manually sculpt the ideal deformation. This method can create the most detailed and refined joints, depending entirely on how the rigger designs them. The downside is that it requires much more work. Every additional degree of freedom requires a significant amount of manual adjustment. These two joint methods have almost opposite characteristics, so in actual Live3D work, I choose the most suitable method depending on the situation. For example, in this hand model, I used Hand-Bent Joints for the arm twisting and fingers, while the wrist uses a Glue Joint.✨

🌀 #Live3D #Live2D #Live2DWIP 🌀 Today, I’d like to share two of the three methods I use to create joint twisting in my Live2D-based 2D Pseudo-3D concept. On the right is the Glue Joint： The basic idea is to use Glue to connect two pseudo-3D ArtMeshes. By taking advantage of Glue’s weight settings, it can create an effect similar to a 3D joint. Once the weights are set up, it can move very freely with a relatively low amount of work. However, it also shares the same weakness as 3D joints: when rotated at large angles, it can produce unpleasant twisting and distortion. On the left is the Hand-Bent Joint： The basic idea is to add bending Keyforms directly to a Warp Deformer, then manually sculpt the ideal deformation. This method can create the most detailed and refined joints, depending entirely on how the rigger designs them. The downside is that it requires much more work. Every additional degree of freedom requires a significant amount of manual adjustment. These two joint methods have almost opposite characteristics, so in actual Live3D work, I choose the most suitable method depending on the situation. For example, in this hand model, I used Hand-Bent Joints for the arm twisting and fingers, while the wrist uses a Glue Joint.✨

📐Hephaestus📏Live2D匠人魂

17,730 Aufrufe • vor 22 Tagen

There are currently 61 humanoid companies spanning 13 countries with a total of 88 humanoids Spent my free time creating an extensive display of humanoid companies to learn the current landscape Opinions: - Super saturated, every developed country fund and build humanoid robots, even developing countries like Vietnam has their own humanoid. - Software is the moat. Breakthrough in software will explode adaptation of robots in both consumer and industry. Observation: - Naming: Robots tends to be named in the following formula: Name + Generation (i.e. MagicBot Gen 1, Vanar Gen 1) or Name + Random Letter + Number (i.e. Jaka K1, Kinisi 01, Unitree G1). - Two diversion in use case: One side focus on utility (Figure, X1, etc.), the other focus on companionship (Enchanted Tools, Andromeda, etc.) Category imo: - Unique Design: Fourier, Enchanted Tools, Slightly Overdone Robotics, Pollen Robotics. - Unique Actuator: Clone Robotics - Best Capabilities: too soon to tell, too much online cherry picked demos instead of real life demonstration. - Most Natural Motion: Cartwheel Robotics, Pollen Robotics. - Highest Cost: Tesla. Hmu or comment below if you want the list.

There are currently 61 humanoid companies spanning 13 countries with a total of 88 humanoids Spent my free time creating an extensive display of humanoid companies to learn the current landscape Opinions: - Super saturated, every developed country fund and build humanoid robots, even developing countries like Vietnam has their own humanoid. - Software is the moat. Breakthrough in software will explode adaptation of robots in both consumer and industry. Observation: - Naming: Robots tends to be named in the following formula: Name + Generation (i.e. MagicBot Gen 1, Vanar Gen 1) or Name + Random Letter + Number (i.e. Jaka K1, Kinisi 01, Unitree G1). - Two diversion in use case: One side focus on utility (Figure, X1, etc.), the other focus on companionship (Enchanted Tools, Andromeda, etc.) Category imo: - Unique Design: Fourier, Enchanted Tools, Slightly Overdone Robotics, Pollen Robotics. - Unique Actuator: Clone Robotics - Best Capabilities: too soon to tell, too much online cherry picked demos instead of real life demonstration. - Most Natural Motion: Cartwheel Robotics, Pollen Robotics. - Highest Cost: Tesla. Hmu or comment below if you want the list.

Binh Pham

65,608 Aufrufe • vor 9 Monaten

NVIDIA DROPPED A MOTION DIFFUSION MODEL FOR HUMANOID ROBOTS trained on 700 hours of mocap data kimodo generates high-quality 3D human and robot motions from text prompts you control it with: → full-body pose keyframes → end-effector positions/rotations → 2D paths and waypoints works on human skeletons and unitree G1 robot plug the outputs directly into mujoco or retarget to other robots using GMR has a web-based interactive demo with a timeline editor. runs locally needs ~17GB VRAM to run inference open source under apache 2.0

NVIDIA DROPPED A MOTION DIFFUSION MODEL FOR HUMANOID ROBOTS trained on 700 hours of mocap data kimodo generates high-quality 3D human and robot motions from text prompts you control it with: → full-body pose keyframes → end-effector positions/rotations → 2D paths and waypoints works on human skeletons and unitree G1 robot plug the outputs directly into mujoco or retarget to other robots using GMR has a web-based interactive demo with a timeline editor. runs locally needs ~17GB VRAM to run inference open source under apache 2.0

Vaishnavi

17,572 Aufrufe • vor 2 Monaten

🚨🇮🇷🇮🇳 For the first time in seven years, an Iranian supertanker has delivered 2 million barrels of crude to India — under a US sanctions waiver. At the same time, the US has announced a naval blockade of the Strait of Hormuz. So on one hand, Washington is restricting Iran’s oil flows — and on the other, it’s allowing shipments to reach India. It may seem contradictory, but the logic is strategic. Keeping India within its orbit matters more than strict consistency. Losing India to a Russia–China energy alignment would be a much bigger problem than the optics of making exceptions.

🚨🇮🇷🇮🇳 For the first time in seven years, an Iranian supertanker has delivered 2 million barrels of crude to India — under a US sanctions waiver. At the same time, the US has announced a naval blockade of the Strait of Hormuz. So on one hand, Washington is restricting Iran’s oil flows — and on the other, it’s allowing shipments to reach India. It may seem contradictory, but the logic is strategic. Keeping India within its orbit matters more than strict consistency. Losing India to a Russia–China energy alignment would be a much bigger problem than the optics of making exceptions.

A K Mandhan

1,212,946 Aufrufe • vor 3 Monaten

Force feedback demo Force feedback is when joystick is pushing on your hand when something is pushing on the robot arm. Feeling the force - so much helpful to control the robot, that done well it allows you to do tasks even without visual feed. You can make an experiment: close your eyes - you can easily get the headphones out of the case. Also, visual information is often not enough. For example, you're trying to pull out a usb connector, but you pull it at the wrong angle, causing it to get stuck. Visually, nothing changes, but the pressure is intense and you can break the connector. Surgical robots have been using force feedback for years, and there are also 3D styluses which use this feature, proving that the technology works and is useful. But in modern robots with AI, it's hardly ever implemented. Although it's useful for both teleoperation and AI model. That's one of the reasons why we are building our robotic arms starting with off the shelf motors rather than taking the whole off the shelf arm. There are still a range of easy wins that can be made iterating robot hardware.

Force feedback demo Force feedback is when joystick is pushing on your hand when something is pushing on the robot arm. Feeling the force - so much helpful to control the robot, that done well it allows you to do tasks even without visual feed. You can make an experiment: close your eyes - you can easily get the headphones out of the case. Also, visual information is often not enough. For example, you're trying to pull out a usb connector, but you pull it at the wrong angle, causing it to get stuck. Visually, nothing changes, but the pressure is intense and you can break the connector. Surgical robots have been using force feedback for years, and there are also 3D styluses which use this feature, proving that the technology works and is useful. But in modern robots with AI, it's hardly ever implemented. Although it's useful for both teleoperation and AI model. That's one of the reasons why we are building our robotic arms starting with off the shelf motors rather than taking the whole off the shelf arm. There are still a range of easy wins that can be made iterating robot hardware.

Igor Kulakov

18,773 Aufrufe • vor 1 Jahr