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A first look at the Forma RaaS Control Interface in action. Live robot state visualization, joint-level control, and task orchestration for 6-DoF arms - all running through a single, web-native dashboard. This control layer is fundamental to Robotics-as-a-Service. It’s what turns robots into remotely accessible, observable, and controllable resources... show more

Forma Robotics

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40,233 görüntüleme • 6 ay önce •via X (Twitter)

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Built Copilot Mission Control to visualize what GitHub Copilot CLI is doing in real time.🌟 It shows: - Active sessions - Tool usage - Input/output tokens - Live activity streams - Replay/time travel - Turns - Full visualization of the entire process A second-monitor dashboard for agent work to look into skills, MCP tools, and more being used. Work in progress - more to come! 🚀

Built Copilot Mission Control to visualize what GitHub Copilot CLI is doing in real time.🌟 It shows: - Active sessions - Tool usage - Input/output tokens - Live activity streams - Replay/time travel - Turns - Full visualization of the entire process A second-monitor dashboard for agent work to look into skills, MCP tools, and more being used. Work in progress - more to come! 🚀

Dan Wahlin

17,395 görüntüleme • 29 gün önce

Another robot from Disney! 🕺🏻 Just look at this dancing fella created by Disney Research. Creating control policies that work on real robots and handling diverse, unseen motions in physics-based character control is still difficult. The Disney team proposes a two-state solution. The first step involves learning a latent space encoding with an autoencoder. After encoding, the policy is trained to map kinematic input to dynamic output, ensuring accurate and adaptable movement. This method eliminates common mode collapse issues and improves motion encoding by separating these stages. This technique has proven effective in real robots in simulations, marking a significant leap forward in robot control. Can't wait for it in action live in 2025 :) ~~~ RT to help 1 robot find a new workplace.

Another robot from Disney! 🕺🏻 Just look at this dancing fella created by Disney Research. Creating control policies that work on real robots and handling diverse, unseen motions in physics-based character control is still difficult. The Disney team proposes a two-state solution. The first step involves learning a latent space encoding with an autoencoder. After encoding, the policy is trained to map kinematic input to dynamic output, ensuring accurate and adaptable movement. This method eliminates common mode collapse issues and improves motion encoding by separating these stages. This technique has proven effective in real robots in simulations, marking a significant leap forward in robot control. Can't wait for it in action live in 2025 :) ~~~ RT to help 1 robot find a new workplace.

Lukas Ziegler

65,887 görüntüleme • 1 yıl önce

Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

20,874 görüntüleme • 4 ay önce

Today we’re using a arm to prototype our first RaaS workflow — soon, the arm doing this will be ours. Using a Franka arm, we prototyped the pick-and-place of Forma logo, a pipeline that will run on the Forma robotic arm: • trajectory planning • precision gripping • closed-loop positioning • object handling It’s our first RaaS workflow running in the real world. We’re building RaaS like software: test → ship → iterate. Next: deploy the same pipeline on the Forma arm and bring automation to the cloud.

Forma Robotics

17,689 görüntüleme • 7 ay önce

QACE Dynamics | Autonomous Navigation Preview Today we are showing autonomous navigation running live inside QACE, the robot plans its route on the map, then adjusts in real time as lidar and vision pick up new obstacles. All of this runs through a single navigation block inside QACE, ready to plug into different robots without touching low-level control. This navigation block is one of the core building pieces of QACE autonomy, and it’s just the first of many we will be rolling out.

QACE Dynamics | Autonomous Navigation Preview Today we are showing autonomous navigation running live inside QACE, the robot plans its route on the map, then adjusts in real time as lidar and vision pick up new obstacles. All of this runs through a single navigation block inside QACE, ready to plug into different robots without touching low-level control. This navigation block is one of the core building pieces of QACE autonomy, and it’s just the first of many we will be rolling out.

Qace Dynamics

12,654 görüntüleme • 7 ay önce

Push a human off balance and they react instantly. Now try building that into a robot… During a recent visit to Hangzhou, hosted by the Zhejiang Provincial Government, we saw a live balance test from Unitree robotics G1 robot. This is where control, perception, and hardware have to move as one in real time.

Push a human off balance and they react instantly. Now try building that into a robot… During a recent visit to Hangzhou, hosted by the Zhejiang Provincial Government, we saw a live balance test from Unitree robotics G1 robot. This is where control, perception, and hardware have to move as one in real time.

Megatron

43,080 görüntüleme • 1 ay önce

Today, we’re introducing KinetIQ, our own AI framework for end-to-end orchestration of humanoid robot fleets. One system, multiple robot embodiments. Industrial, service and home environments coordinated in real time. The framework consists of 4 cognitive layers: from high-level task allocation and workflow optimisation down to VLA-based task execution and RL-trained whole-body control. Watch how KinetIQ runs both our wheeled and bipedal robots. Read more on our blog:

Today, we’re introducing KinetIQ, our own AI framework for end-to-end orchestration of humanoid robot fleets. One system, multiple robot embodiments. Industrial, service and home environments coordinated in real time. The framework consists of 4 cognitive layers: from high-level task allocation and workflow optimisation down to VLA-based task execution and RL-trained whole-body control. Watch how KinetIQ runs both our wheeled and bipedal robots. Read more on our blog:

Humanoid

23,887 görüntüleme • 4 ay önce

How do you give a humanoid the general motion capability? Not just single motions, but all motion? Introducing SONIC, our new work on supersizing motion tracking for natural humanoid control. We argue that motion tracking is the scalable foundation task for humanoids. So we "supersized" it: 9k+ GPU hours and 100M+ motion frames. But tracking alone is not enough; we show how to make a useful control system out of it: - Universal Kinematic Planner: Enables game-like gamepad control and high-level teleoperation, just like controlling a character in a game. - VR Full-Body Teleop: Direct, real-time whole-body control by a human wearing a VR headset. - VR Keypoint Teleop: Control the upper body (hands/head) while our planner handles robust locomotion automatically. - VLA Integration: We connect this motion tracker to autonomous Visual-Language-Action (VLA) models for autonomous task execution! We use a Universal Token Space to UNIFY this command space, turning our robust tracker into a general-purpose, programmable humanoid brain. This is the generalist "System 1" for humanoids. 🚀 Project: #Humanoids #Robotics #AI #FoundationModels #NVIDIAResearch 🧠🔥

How do you give a humanoid the general motion capability? Not just single motions, but all motion? Introducing SONIC, our new work on supersizing motion tracking for natural humanoid control. We argue that motion tracking is the scalable foundation task for humanoids. So we "supersized" it: 9k+ GPU hours and 100M+ motion frames. But tracking alone is not enough; we show how to make a useful control system out of it: - Universal Kinematic Planner: Enables game-like gamepad control and high-level teleoperation, just like controlling a character in a game. - VR Full-Body Teleop: Direct, real-time whole-body control by a human wearing a VR headset. - VR Keypoint Teleop: Control the upper body (hands/head) while our planner handles robust locomotion automatically. - VLA Integration: We connect this motion tracker to autonomous Visual-Language-Action (VLA) models for autonomous task execution! We use a Universal Token Space to UNIFY this command space, turning our robust tracker into a general-purpose, programmable humanoid brain. This is the generalist "System 1" for humanoids. 🚀 Project: #Humanoids #Robotics #AI #FoundationModels #NVIDIAResearch 🧠🔥

Zhengyi “Zen” Luo

61,889 görüntüleme • 7 ay önce

A humanoid robot playing a Yamaha drum kit is one of the cleanest ways to test rhythm control in public. Drumming exposes timing, wrist motion, impact force, arm recovery, and coordination between both hands. Even if the routine is pre-programmed or assisted, the useful part is visible: the robot has to strike, reset, and stay in rhythm without turning into random arm movement. Robot musicians may look funny today. They are quietly testing the same control problems needed for household robots, factory arms, and physical AI systems that work around humans. Would you call this entertainment, robotics research, or the early market for robot performers?

A humanoid robot playing a Yamaha drum kit is one of the cleanest ways to test rhythm control in public. Drumming exposes timing, wrist motion, impact force, arm recovery, and coordination between both hands. Even if the routine is pre-programmed or assisted, the useful part is visible: the robot has to strike, reset, and stay in rhythm without turning into random arm movement. Robot musicians may look funny today. They are quietly testing the same control problems needed for household robots, factory arms, and physical AI systems that work around humans. Would you call this entertainment, robotics research, or the early market for robot performers?

TechniaHQ | humanoid robots

208,048 görüntüleme • 27 gün önce

One operator. Multiple live feeds. Total control. Our strike deck software lets you monitor multiple drones in real time, set waypoints on the fly, select targets, and execute precision strikes, all from a single interface. This is what scalable drone operations actually look like. #dronedominance #cuas #droneswarm #drones #dronewarfare

One operator. Multiple live feeds. Total control. Our strike deck software lets you monitor multiple drones in real time, set waypoints on the fly, select targets, and execute precision strikes, all from a single interface. This is what scalable drone operations actually look like. #dronedominance #cuas #droneswarm #drones #dronewarfare

Swarm Defense

18,441 görüntüleme • 3 ay önce

A robot from NASA with a bionic hand! 🧑🏼‍🚀 Giving a humanoid more dexterity with a PSYONIC ability hand! NASA Valkyrie robot, standing at 1.8 meters tall and weighing 125 kg, is a bipedal humanoid designed to perform tasks in dangerous environments on Earth and in space. Valkyrie is part of NASA's efforts to enhance remote control technologies and develop fully autonomous robots. 🕹️ The goal is to allow astronauts to supervise hazardous work remotely and delegate repetitive tasks to robots. This approach can help them work on more complex tasks, even in locations where astronauts are not physically present. P.S. NASA plans to deploy Valkyrie on the Moon for long-term work and habitats during Artemis missions, even without astronauts.

A robot from NASA with a bionic hand! 🧑🏼‍🚀 Giving a humanoid more dexterity with a PSYONIC ability hand! NASA Valkyrie robot, standing at 1.8 meters tall and weighing 125 kg, is a bipedal humanoid designed to perform tasks in dangerous environments on Earth and in space. Valkyrie is part of NASA's efforts to enhance remote control technologies and develop fully autonomous robots. 🕹️ The goal is to allow astronauts to supervise hazardous work remotely and delegate repetitive tasks to robots. This approach can help them work on more complex tasks, even in locations where astronauts are not physically present. P.S. NASA plans to deploy Valkyrie on the Moon for long-term work and habitats during Artemis missions, even without astronauts.

Lukas Ziegler

20,512 görüntüleme • 1 yıl önce

🚀 Launching our open-source teleoperation device for full-body Vega robot control! 🔓 Open-source 💰 Low-cost 🎒 Portable 🦾 Whole-body control Control both real and simulated Vega robots! 🤖✨ 📍 Live Demo at #CoRL - See it in action with real and simulated Vega robots in Isaac Lab. Stop by booth #6 if you're attending! #PhysicalAI #Robotics #Teleoperation

🚀 Launching our open-source teleoperation device for full-body Vega robot control! 🔓 Open-source 💰 Low-cost 🎒 Portable 🦾 Whole-body control Control both real and simulated Vega robots! 🤖✨ 📍 Live Demo at #CoRL - See it in action with real and simulated Vega robots in Isaac Lab. Stop by booth #6 if you're attending! #PhysicalAI #Robotics #Teleoperation

Dexmate

14,087 görüntüleme • 8 ay önce

Democratizing access to robotics! ⚖️ Nowadays anyone, literally anyone, can develop robotic projects using hardware. Robots are associated with a capital-intensive investment. Not anymore. This arm from The Robot Studio (16 DoF in hand, 7 DoF in arm) can be purchased for less than $450! 😮‍💨 If we consider this fully open-source ⎯ , then I think you'll agree that it is one of the best ways to get started with robotics and AI. In this application, thanks to the haptic glove, the operator can remotely control the robot in real-time. 🧤 Hugging Face making it all possible! 🔥 Kudos Remi Cadene & team! ~~~ ♻️ RT to help 1 robot find a new workplace.

Democratizing access to robotics! ⚖️ Nowadays anyone, literally anyone, can develop robotic projects using hardware. Robots are associated with a capital-intensive investment. Not anymore. This arm from The Robot Studio (16 DoF in hand, 7 DoF in arm) can be purchased for less than $450! 😮‍💨 If we consider this fully open-source ⎯ , then I think you'll agree that it is one of the best ways to get started with robotics and AI. In this application, thanks to the haptic glove, the operator can remotely control the robot in real-time. 🧤 Hugging Face making it all possible! 🔥 Kudos Remi Cadene & team! ~~~ ♻️ RT to help 1 robot find a new workplace.

Lukas Ziegler

15,420 görüntüleme • 1 yıl önce

In this example, you can see a gravity-compensated 2 DOF robot. This concept is being used in all modern robots and we want to bring this exact technology to user affordable robots. Previously we made it with 1 DOF arm now with 2 DOF next is 6-7 DOF robots! Stay tuned!

In this example, you can see a gravity-compensated 2 DOF robot. This concept is being used in all modern robots and we want to bring this exact technology to user affordable robots. Previously we made it with 1 DOF arm now with 2 DOF next is 6-7 DOF robots! Stay tuned!

SourceRobotics

17,310 görüntüleme • 1 yıl önce

Everyone is talking about OpenClaw mission controls. I rebuilt a $250K mission control using only one prompt. In this video you'll see: •The 3 levels of mission controls real builders are running •Why a mission control is critical to OpenClaw success •The exact prompt I used to generate the full dashboard in Lovable •My agent creating tasks in real time on the board instantly The full video is live on YouTube. Comment "Mission" and I'll DM you the link.

Everyone is talking about OpenClaw mission controls. I rebuilt a $250K mission control using only one prompt. In this video you'll see: •The 3 levels of mission controls real builders are running •Why a mission control is critical to OpenClaw success •The exact prompt I used to generate the full dashboard in Lovable •My agent creating tasks in real time on the board instantly The full video is live on YouTube. Comment "Mission" and I'll DM you the link.

Jacob Klug

27,924 görüntüleme • 4 ay önce

The Network Builder auctions are LIVE. For the first time, individuals and businesses can step forward to actively participate in building decentralized mobile infrastructure. This is what DePIN looks like when it moves from theory to execution. From interest to action. From maps to real-world networks. The next phase starts now. 👉 Learn how to bid 👇

The Network Builder auctions are LIVE. For the first time, individuals and businesses can step forward to actively participate in building decentralized mobile infrastructure. This is what DePIN looks like when it moves from theory to execution. From interest to action. From maps to real-world networks. The next phase starts now. 👉 Learn how to bid 👇

World Mobile

32,733 görüntüleme • 5 ay önce

Robots might learn better from video than from language! 📼 Most Vision-Language-Action (VLA) models learn what to do from text, but still struggle with how things move in the real world. That makes them data-hungry and slow to train. mimic video takes a different route. Instead of grounding robot control in text, it grounds it in video, using large pre-trained video models that already capture physical motion and dynamics. The idea is straightforward: let the video model handle “what will happen next,” and let a smaller control model focus only on turning that visual plan into robot actions. The result is big gains in practice. Robots trained this way need 10× less data, converge twice as fast, and perform better on both simulated benchmarks and real bimanual manipulation tasks. If robots can “imagine” motion using video, control becomes a much simpler problem. Shoutout to Jonas Pai, Liam Achenbach, Oier Mees, Elvis Nava and the rest of the team! Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Robots might learn better from video than from language! 📼 Most Vision-Language-Action (VLA) models learn what to do from text, but still struggle with how things move in the real world. That makes them data-hungry and slow to train. mimic video takes a different route. Instead of grounding robot control in text, it grounds it in video, using large pre-trained video models that already capture physical motion and dynamics. The idea is straightforward: let the video model handle “what will happen next,” and let a smaller control model focus only on turning that visual plan into robot actions. The result is big gains in practice. Robots trained this way need 10× less data, converge twice as fast, and perform better on both simulated benchmarks and real bimanual manipulation tasks. If robots can “imagine” motion using video, control becomes a much simpler problem. Shoutout to Jonas Pai, Liam Achenbach, Oier Mees, Elvis Nava and the rest of the team! Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

49,920 görüntüleme • 6 ay önce

Triple inverted pendulum in transition control A classic control problem, done in real time. This setup moves smoothly between all eight equilibrium points of a triple inverted pendulum. The system reacts every 1 millisecond, which shows how fast modern control loops can be. • Real-time control at 1 ms sampling • Stable transitions between multiple balance points • Built with Simulink and LW-RCP02 hardware This is a beautiful example of how theory meets practice in advanced control engineering. Video: Credit: Embedded Control Lab, Inha University —- Weekly robotics and AI insights. Subscribe free:

Triple inverted pendulum in transition control A classic control problem, done in real time. This setup moves smoothly between all eight equilibrium points of a triple inverted pendulum. The system reacts every 1 millisecond, which shows how fast modern control loops can be. • Real-time control at 1 ms sampling • Stable transitions between multiple balance points • Built with Simulink and LW-RCP02 hardware This is a beautiful example of how theory meets practice in advanced control engineering. Video: Credit: Embedded Control Lab, Inha University —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

167,740 görüntüleme • 5 ay önce

ICYMI: Robotics history live on the community update yesterday. A pair of @Mentraglass was used to control robots by Unitree and PadBot through the Follow @Auki App-agnostic, device-agnostic spatial orchestration. We are hiring.

ICYMI: Robotics history live on the community update yesterday. A pair of @Mentraglass was used to control robots by Unitree and PadBot through the Follow @Auki App-agnostic, device-agnostic spatial orchestration. We are hiring.

Nils

34,061 görüntüleme • 8 ay önce