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This robodog aims to remove humans from hazardous work environments The Robot Teleoperativo 2 project out of the Dynamic Legged Systems lab has developed an advanced teleoperation system designed to operate in high-risk environments, minimizing dangers to human workers. By integrating cutting-edge technologies in tele-locomotion, tele-manipulation, and remote human-robot...

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Circuit

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22,831 görüntüleme • 1 yıl önce •via X (Twitter)

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AI_TechnoKing profil fotoğrafı
AI_TechnoKing1 yıl önce

Cool design, I need one to empty my recycling bins, they are practically a bio hazard!☣️

UserInterface profil fotoğrafı
UserInterface2 yıl önce

Unveiling the Future of Prompt Engineering for Better AI Interactions #tech

Abhinav Girdhar profil fotoğrafı
Abhinav Girdhar1 yıl önce

A huge step toward safer workplaces! Keeping humans out of harm’s way with advanced teleoperation.

Victor profil fotoğrafı
Victor1 yıl önce

dogs were just beta testing robots all along - nature knew what it was doing when it made them our best friends

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🚨 Noida-based EndureAir Systems has combined its UAV tech with Addverb Technologies’ quadruped robot to demonstrate autonomous reconnaissance capabilities. This integrated system can enter confined and hazardous zones first, giving forces safer reach in high-risk environments.

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This is Delta, a deformable multirotor robot developed by scientists at the University of Tokyo that can both fly and roll using its flexible body design. It uses a thrust control system to move efficiently in the air and on the ground, allowing it to adapt to different environments. This capability makes it useful for tasks like disaster response and long-duration operations, introduced in 2024.

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Shanghai-based iSAGE is teasing what it calls the world’s first “spatial heterogenous” six-armed humanoid robot. The Hexa-Arm Robot is designed for crowded factory workstations where several tasks must be completed quickly and precisely. Each of its arms can reportedly operate in its own area on different jobs. The system has 120 moving joints, force control on every arm, and advanced cameras for assembly tasks.

Mike Kalil

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Teaching robots to perform dexterous manipulation tasks currently requires teleoperation, which limits demonstration quality, speed, and scalability. Instead, why not use human videos? The problem is that a human hand isn’t a robot hand, so data must be retargeted using simulation to resolve issues like collisions and interpenetration when controlling the hand. In VideoManip, Hongyi Chen and co-authors built a system to solve this problem, taking in RGB videos of humans performing manipulation tasks and using them to create accurate simulations with which to learn robot policies. Watch episode #73 of RoboPapers, hosted by Michael Cho - Rbt/Acc and Chris Paxton, now to learn more!
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Teaching robots to perform dexterous manipulation tasks currently requires teleoperation, which limits demonstration quality, speed, and scalability. Instead, why not use human videos? The problem is that a human hand isn’t a robot hand, so data must be retargeted using simulation to resolve issues like collisions and interpenetration when controlling the hand. In VideoManip, Hongyi Chen and co-authors built a system to solve this problem, taking in RGB videos of humans performing manipulation tasks and using them to create accurate simulations with which to learn robot policies. Watch episode #73 of RoboPapers, hosted by Michael Cho - Rbt/Acc and Chris Paxton, now to learn more!

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Happy #NationalRoboticsWeek! Last year, we gave you a sneak peek at AthenaZero, our robotic manipulator built to tackle dynamic tasks like a human arm. Learn more about how this fast, precise robot can switch in an instant from a gentle touch to high force depending on what the task requires:

RAI Institute

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Just collecting manipulation data isn’t enough for robots - they need to be able to move around in the world, which has a whole different set of challenges from pure manipulation. And bringing navigation and manipulation together in a single framework is even more challenging. Enter HERMES, from Zhecheng Yuan and Tianming Wei. This is a four-stage process in which human videos are used to set up an RL sim-to-real training pipeline in order to overcome differences between robot and human kinematics, and used together with a navigation foundation model to move around in a variety of environments. To learn more, join us as Zhecheng Yuan and Tianming Wei tell us about how they built their system to perform mobile dexterous manipulation from human videos in a variety of environments. Watch Episode #45 of RoboPapers today, hosted by Michael Cho - Rbt/Acc and Chris Paxton!

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LIGHTYEAR ROBOTICS has officially launched the M1, their first wheeled-legged robot. The M1 utilizes a self-developed parallel joint drive module, achieving a 40% efficiency increase over traditional structures while keeping the body lightweight. The design balances two core performance features: off-road mobility and high-speed cruising, enabling it to navigate complex environments like grass, gravel, and steep slopes using its all-scenario intelligent perception and autonomous navigation system. The robot is primarily aimed at enterprise applications, providing unmanned and highly reliable solutions for tasks ranging from outdoor inspection and emergency detection to material transport in challenging environments. #AI #HumanoidRobot #EmbodiedAI

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VLAI Robotics Launches High-Dexterity Dual-Arm Robot Starting at ~$5,500 USD VLAI Robotics, utilizing the open-source design of Japan’s OpenArm team, has introduced a high-dexterity, low-cost bimanual robotic system. The product is priced from 39,900 RMB (approximately 5,500 USD), making high-level research tools accessible to institutions and developers. The robot features a human-scale, arm-hand integrated design with up to 16 DOF (8 DOF per arm, including the gripper). It can handle a dual-arm peak payload of 12 kg while maintaining high precision. A key breakthrough is its ability to replicate human upper limb movement trajectories, which enhances data quality for imitation learning and remote operation. VLAI Robotics handled the domestic engineering, manufacturing, and VLA (Vision-Language-Action) algorithm integration, with quality control organized according to the strict standards of the OpenArm R&D framework. The robot is highly adaptable for research, education, and Physical AI training, supporting easy expansion for features like VR teleoperation.
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Meet Foodly, the humanoid collaborative robot by RT Corporation! This compact dual-arm robot is designed for food factories, working alongside humans to enhance efficiency and hygiene. With its AI vision system, Foodly can recognize and pick up bulk ingredients, ensuring precise assembly. It promotes safe collaboration on production lines, reduces labor shortages, and minimizes contamination risks. Easy to operate and mobile, Foodly adapts to various production needs.

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Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!
1:07

Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!

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