Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

New research: Quadruped robots climbing ladders! 🦾🚀 Using RL-based control and a hooked end-effector, we're expanding robot capabilities in industrial environments. More info in the paper: Video:

Robotic Systems Lab

26,895 subscribers

16,390 views • 1 year ago •via X (Twitter)

Health & Wellness Science & Technology Education

Anya Rossi• Live Now

Private livecam show

4 Comments

Synthical1 year ago

Dark mode for this paper for those who read at night 🌚

Anthund1 year ago

so no safe place in the robots apocalypse.

Kordel France1 year ago

Wow, that robustness is very difficult to simulate, let alone achieve in reality. Well done!

Saar Reshef1 year ago

Cool

Related Videos

A new paper by Disney Research introduces a 2-stage technique for motion tracking in physics-based character animation, using a pretrained latent space and RL to control diverse and unseen motions on both virtual and real-world humanoid robots. Paper:

A new paper by Disney Research introduces a 2-stage technique for motion tracking in physics-based character animation, using a pretrained latent space and RL to control diverse and unseen motions on both virtual and real-world humanoid robots. Paper:

The Humanoid Hub

20,051 views • 1 year ago

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 views • 4 months ago

Wouldn't it be great if we could train robots without any teleoperation! In our latest paper, we train robots to mimic a human video of the task by simply matching the object features using RL. We only need one video and under an hour of robot training.

Wouldn't it be great if we could train robots without any teleoperation! In our latest paper, we train robots to mimic a human video of the task by simply matching the object features using RL. We only need one video and under an hour of robot training.

Lerrel Pinto

46,197 views • 1 year ago

This research from ETH Zurich examines advancements in quadruped robots for industrial settings, specifically addressing their ability to climb ladders—a previously overlooked but essential capability. While legged robots excel over wheeled robots on rough terrain, their inability to scale ladders has limited their effectiveness in inspecting dangerous areas, impacting both safety and efficiency. Credit: ETH Zurich #engineering #technology #robotics #robots -------------------------------- Stay ahead of the curve! Follow us now on our WhatsApp ( and Telegram ( channels and stay updated about the cutting edge.

This research from ETH Zurich examines advancements in quadruped robots for industrial settings, specifically addressing their ability to climb ladders—a previously overlooked but essential capability. While legged robots excel over wheeled robots on rough terrain, their inability to scale ladders has limited their effectiveness in inspecting dangerous areas, impacting both safety and efficiency. Credit: ETH Zurich #engineering #technology #robotics #robots -------------------------------- Stay ahead of the curve! Follow us now on our WhatsApp ( and Telegram ( channels and stay updated about the cutting edge.

Wevolver

10,615 views • 11 months ago

PNDBotics’ humanoid robot Adam tackles difficult terrain using an RL-based control policy.

PNDBotics’ humanoid robot Adam tackles difficult terrain using an RL-based control policy.

The Humanoid Hub

26,656 views • 1 year ago

More humanoid robots from China! Beijing-based industrial robot maker ROKAE Robotics has unveiled two humanoid robot models.

More humanoid robots from China! Beijing-based industrial robot maker ROKAE Robotics has unveiled two humanoid robot models.

The Humanoid Hub

18,137 views • 11 months ago

Learning H-Infinity Locomotion Control Stable locomotion in precipitous environments is an essential capability of quadruped robots, demanding the ability to resist various external disturbances. However, recent learning-based policies only use basic domain randomization to

Learning H-Infinity Locomotion Control Stable locomotion in precipitous environments is an essential capability of quadruped robots, demanding the ability to resist various external disturbances. However, recent learning-based policies only use basic domain randomization to

AK

38,603 views • 2 years ago

Excited to share a new humanoid robot platform we’ve been working on. Berkeley Humanoid is a reliable and low-cost mid-scale research platform for learning-based control. We demonstrate the robot walking on various terrains and dynamic hopping with a simple RL controller.

Excited to share a new humanoid robot platform we’ve been working on. Berkeley Humanoid is a reliable and low-cost mid-scale research platform for learning-based control. We demonstrate the robot walking on various terrains and dynamic hopping with a simple RL controller.

Qiayuan Liao

80,294 views • 1 year ago

Co-CEO Weekly Update 045 FF continues expanding the real-world deployment of its EAI Robotics ecosystem with new deliveries and scenario expansion. ① FF completed delivery of the Master robot and pilot delivery of the Aegis robot to Texas-based NS Federation, expanding real-world EAI Robotics deployment. ② The delivery introduces two new “Robot + Vehicle +” application scenarios: education and performance, backed by real market demand. ③ In “Robot & Vehicle + Education,” EAI robots support robotics training, research assistance, data collection, and hands-on AI education across schools, labs, and research institutions. ④ In “Robot & Vehicle + Performance,” robots serve as interactive performers for events, competitions, and entertainment environments—unlocking new consumer and light commercial markets. ⑤ On the EAI EV side, FF leadership held discussions in Washington, D.C. with the U.S. Department of Transportation and Department of Commerce on tariff policy, industry development, and technology innovation. #FFAI #AIXC #Robotics #FaradayFuture

Co-CEO Weekly Update 045 FF continues expanding the real-world deployment of its EAI Robotics ecosystem with new deliveries and scenario expansion. ① FF completed delivery of the Master robot and pilot delivery of the Aegis robot to Texas-based NS Federation, expanding real-world EAI Robotics deployment. ② The delivery introduces two new “Robot + Vehicle +” application scenarios: education and performance, backed by real market demand. ③ In “Robot & Vehicle + Education,” EAI robots support robotics training, research assistance, data collection, and hands-on AI education across schools, labs, and research institutions. ④ In “Robot & Vehicle + Performance,” robots serve as interactive performers for events, competitions, and entertainment environments—unlocking new consumer and light commercial markets. ⑤ On the EAI EV side, FF leadership held discussions in Washington, D.C. with the U.S. Department of Transportation and Department of Commerce on tariff policy, industry development, and technology innovation. #FFAI #AIXC #Robotics #FaradayFuture

YT Jia 贾跃亭

16,235 views • 3 months ago

The robot climbs stairs🏯, steps over stones 🪨, and runs in the wild🏞️, all in one policy, without any remote control! Our #CVPR2023 Highlight paper achieves this by using RL + a 3D Neural Volumetric Memory (NVM) trained with view synthesis!

The robot climbs stairs🏯, steps over stones 🪨, and runs in the wild🏞️, all in one policy, without any remote control! Our #CVPR2023 Highlight paper achieves this by using RL + a 3D Neural Volumetric Memory (NVM) trained with view synthesis!

Xiaolong Wang

113,006 views • 3 years ago

Check out our #ICRA2024 paper "Actor-Critic Model Predictive Control." Model-free #reinforcementlearning (RL) is known for its strong task performance and flexibility in optimizing general reward formulations. On the other hand, #ModelPredictiveControl (MPC) benefits from robustness and online replanning capabilities. We combine both approaches by introducing a new framework called Actor-Critic Model Predictive Control. The key idea is to embed a differentiable MPC within an Actor-Critic RL framework. The proposed approach leverages the short-term predictive optimization capabilities of MPC with the exploratory and end-to-end training properties of RL. The resulting policy effectively manages both short-term decisions through the MPC-based actor and long-term prediction via the critic network, unifying the benefits of both model-based control and end-to-end learning. We validate our method in simulation and the real world with a quadcopter across various high-level tasks. We show that the proposed architecture can achieve real-time control performance, learn complex behaviors via trial and error, and retain the predictive properties of the MPC to better handle out-of-distribution behavior. Paper: Full Video with more details: Kudos to Ángel Romero, Yunlong Song IEEE ICRA University of Zurich UZH Science UZH Space Hub Aerial Core AUTOASSESS European Research Council (ERC)

Check out our #ICRA2024 paper "Actor-Critic Model Predictive Control." Model-free #reinforcementlearning (RL) is known for its strong task performance and flexibility in optimizing general reward formulations. On the other hand, #ModelPredictiveControl (MPC) benefits from robustness and online replanning capabilities. We combine both approaches by introducing a new framework called Actor-Critic Model Predictive Control. The key idea is to embed a differentiable MPC within an Actor-Critic RL framework. The proposed approach leverages the short-term predictive optimization capabilities of MPC with the exploratory and end-to-end training properties of RL. The resulting policy effectively manages both short-term decisions through the MPC-based actor and long-term prediction via the critic network, unifying the benefits of both model-based control and end-to-end learning. We validate our method in simulation and the real world with a quadcopter across various high-level tasks. We show that the proposed architecture can achieve real-time control performance, learn complex behaviors via trial and error, and retain the predictive properties of the MPC to better handle out-of-distribution behavior. Paper: Full Video with more details: Kudos to Ángel Romero, Yunlong Song IEEE ICRA University of Zurich UZH Science UZH Space Hub Aerial Core AUTOASSESS European Research Council (ERC)

Davide Scaramuzza

34,874 views • 2 years ago

Another American industrial humanoid robot🤖🏭 Noble Machines (formerly UCR) has just emerged from stealth mode. Launching the first humanoid robot. Founded only 18 months ago, it has already been deployed in a Fortune Global 500 factory. Teams from SpaceX, NASA, and Apple specialize in the toughest, most tiring, and most dangerous industrial tasks: >27kg heavy load >5-hour battery life >Walking speed 0.8m/s >Climbing stairs, traversing scaffolding, and navigating chaotic construction sites > Modular end effector, allowing for quick tool change. > AI-controlled operation with end-to-end autonomy; learns new skills in hours >Autonomous operation + Telep-op mode >Rapid integration with existing enterprise workflows > Human-robot collaboration

Another American industrial humanoid robot🤖🏭 Noble Machines (formerly UCR) has just emerged from stealth mode. Launching the first humanoid robot. Founded only 18 months ago, it has already been deployed in a Fortune Global 500 factory. Teams from SpaceX, NASA, and Apple specialize in the toughest, most tiring, and most dangerous industrial tasks: >27kg heavy load >5-hour battery life >Walking speed 0.8m/s >Climbing stairs, traversing scaffolding, and navigating chaotic construction sites > Modular end effector, allowing for quick tool change. > AI-controlled operation with end-to-end autonomy; learns new skills in hours >Autonomous operation + Telep-op mode >Rapid integration with existing enterprise workflows > Human-robot collaboration

CyberRobo

44,656 views • 3 months ago

Fastest quadruped robot on Earth! 🐆 It's been more than a decade since that gasoline-powered robot was created by the Boston Dynamics team. The WildCat, a quadruped robot was unveiled in a surprising video in 2013 demonstrating its ability to run at speeds of up to 25 km/h on various terrains, showcasing bounding and galloping gaits. Developed based on the Cheetah robot, WildCat was part of Boston Dynamics' efforts funded by one of the DARPA's programs. You know very well what their actual quadruped robot - Spot - looks like. It seems to me that these days - a decade in robotics, can change everything. Just look at the different projects of humanoid robots. Quite a journey as you look at Spot today :-) ♻️ RT to help 1 robot find a new workplace!

Fastest quadruped robot on Earth! 🐆 It's been more than a decade since that gasoline-powered robot was created by the Boston Dynamics team. The WildCat, a quadruped robot was unveiled in a surprising video in 2013 demonstrating its ability to run at speeds of up to 25 km/h on various terrains, showcasing bounding and galloping gaits. Developed based on the Cheetah robot, WildCat was part of Boston Dynamics' efforts funded by one of the DARPA's programs. You know very well what their actual quadruped robot - Spot - looks like. It seems to me that these days - a decade in robotics, can change everything. Just look at the different projects of humanoid robots. Quite a journey as you look at Spot today :-) ♻️ RT to help 1 robot find a new workplace!

Lukas Ziegler

32,099 views • 1 year ago

🤖 New paper: MobileVLA-R1 A unified VLA system that brings real reasoning + continuous control to quadruped robots. CoT dataset, 2-stage training, real-world deployment. 📄paper & code & demo:

🤖 New paper: MobileVLA-R1 A unified VLA system that brings real reasoning + continuous control to quadruped robots. CoT dataset, 2-stage training, real-world deployment. 📄paper & code & demo:

Hao Tang (hiring postdocs)

27,232 views • 6 months ago

Introducing INTELLECT-3: Scaling RL to a 100B+ MoE model on our end-to-end stack Achieving state-of-the-art performance for its size across math, code and reasoning Built using the same tools we put in your hands, from environments & evals, RL frameworks, sandboxes & more

Introducing INTELLECT-3: Scaling RL to a 100B+ MoE model on our end-to-end stack Achieving state-of-the-art performance for its size across math, code and reasoning Built using the same tools we put in your hands, from environments & evals, RL frameworks, sandboxes & more

Prime Intellect

1,133,644 views • 6 months ago

Germany-based Agile Robots has introduced its humanoid robot, Agile One, designed for industrial environments. It features a dexterous robotic hand and runs on a physical AI system trained using real factory data, allowing it to work and interact autonomously. The company is now aiming to move Agile One into full-scale production.

Germany-based Agile Robots has introduced its humanoid robot, Agile One, designed for industrial environments. It features a dexterous robotic hand and runs on a physical AI system trained using real factory data, allowing it to work and interact autonomously. The company is now aiming to move Agile One into full-scale production.

Space and Technology

37,351 views • 2 months ago

Imagine robots learning new skills—without any robot data. Today, we're excited to release EgoZero: our first steps in training robot policies that operate in unseen environments, solely from data collected through humans wearing Aria smart glasses. 🧵👇

Imagine robots learning new skills—without any robot data. Today, we're excited to release EgoZero: our first steps in training robot policies that operate in unseen environments, solely from data collected through humans wearing Aria smart glasses. 🧵👇

Lerrel Pinto

42,538 views • 1 year ago

Figure says it has increased humanoid robot production from one robot per day to one robot per hour in just 120 days. The robots undergo intensive testing, including repeated squats and jogging movements. Figure also demonstrated the robot's ability to climb stairs and navigate complex terrain using vision-based control.

Figure says it has increased humanoid robot production from one robot per day to one robot per hour in just 120 days. The robots undergo intensive testing, including repeated squats and jogging movements. Figure also demonstrated the robot's ability to climb stairs and navigate complex terrain using vision-based control.

Space and Technology

538,320 views • 10 days ago

Scientists have developed a neural network-based planning framework that enables robots to navigate complex environments and mazes autonomously. Learn more in Science Robotics:

Scientists have developed a neural network-based planning framework that enables robots to navigate complex environments and mazes autonomously. Learn more in Science Robotics:

Science Magazine

25,783 views • 11 months ago