Introducing 2️⃣ new AI systems for robotics: 🤖 ALOHA... Unleashed to perform two-armed manipulation tasks 🦾 DemoStart to control a multi-fingered robotic hand They learned to tackle a range of actions requiring dexterity. Here's how. 🧵show more

How can non-experts quickly teach robots a variety of... tasks? Introducing HAND ✋, a simple, time-efficient method of training robots! Using just a **single hand demo**, HAND learns manipulation tasks in under **4 minutes**! 🧵show more

We’re helping robots self-improve with the power of LLMs.... 🤖 Introducing the Summarize, Analyze, Synthesize (SAS) prompt, which analyzes how they perform tasks based on previous actions and then suggests ways for them to get better using the medium of table tennis. 🏓show more

Introducing CQN: Coarse-to-fine Q-Network, a value-based RL algorithm for... continuous control🦾Initialized with 20~50 demonstrations, it learns to solve real-world robotic tasks within 10 mins of training, without any pre-training and shaped rewards! (1/4)show more

✨ Any static 3D assets ➡️ 4D dynamic worlds.... Introducing CHORD, a universal framework for generating scene-level 4D dynamic motion from any static 3D inputs. It generalizes surprisingly well across a wide range of objects 🤯 and can even be used to learn robotics manipulation policy 🤖! Project page: Dive deeper in a 🧵: 1/nshow more

🤖 Can a single robot policy manipulate diverse tools... without ever seeing them before? Introducing SimToolReal 🔨 : a generalist dexterous manipulation policy that transfers zero-shot sim→real to unseen tools + unseen tasks All videos are 1x speed (60 Hz control) 🧵👇show more

Modern robotic wrist joints often use timing belt differentials... to achieve smooth, multi-axis movement within compact spaces. By distributing motion through synchronized belt systems, a single actuator can control multiple rotational outputs with high precision. This design reduces weight, minimizes backlash, and allows for more efficient force transmission compared to traditional gear-based systems. It is widely used in robotic arms where accuracy, responsiveness, and compactness are critical. The result is more natural, fluid motion-bringing robotic systems closer to human-like dexterity in industrial and automation applications.show more

BaBot: A Ball-Balancing Robotics Kit BaBot is a do-it-yourself... ball-balancing robot kit designed as a hands-on platform for learning robotics and control systems. It enables users to explore concepts such as PID control, sensors, actuators, and software integration through practical experimentation. The kit is intended for students, makers, and others interested in applied robotics without requiring a formal engineering background. Credit: Babot Project #arduino #ai #robotics #3dprint #engineeringshow more

Introducing AISY: The AI Agent Network Layer for Everyone... AISY revolutionizes how you build, deploy, and monetize AI agents. 🤖 From automating tasks to scaling operations, AISY makes AI accessible to individuals and businesses alike.show more

Humanoids. Quadrupeds. Industrial robots. Two days of physical AI... innovation. 🤖 At #AdvancingAI, our robotics customers and partners showcased how AMD embedded technology is helping bring intelligent, autonomous systems from concept to real-world deployment.show more

How could robotics soon help us in our daily... lives? 🤖 Today, we’re announcing a suite of research advances that enable robots to make decisions faster as well as better understand and navigate their environments. Here's a snapshot of the work. 🧵show more

Humanoids 🤖 will do anything humans can do. But... are state-of-the-art algorithms up to the challenge? Introducing HumanoidBench, the first-of-its-kind simulated humanoid benchmark with 27 distinct whole-body tasks requiring intricate long-horizon planning and coordination. 🧵👇show more

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:show more

Imitation learning is powerful, but hard to scale due... to lack of high quality data. Introducing Optimus: TAMP-supervised visuomotor transformers. Optimus solves over 300 long-horizon manipulation tasks with up to 8 stages and 72 different objects. NVIDIA AI Developer CMU Robotics Institute 1/Nshow more

China doing China things.. A new robotic traffic controller... is being tested in multiple locations. 🤖🦾show more

🧵 Houston, we have liftoff! 🎉🐦 Welcome to the... new era of gamified options trading with FLIP! Dive in to find out more about how we're introducing a multi-dimensional trading experience for the courageous, the curious, and the adventurous 👉show more

Super excited to feature TWO exciting AGI projects using... GPT News 🔥⚡️ 🤖 llama_agi: Automatically execute tasks towards a goal! ⚙️ auto_llama: An internet agent to fulfill tasks. Link: GPT News makes AGI projects straightforward to build. 🧵show more

they finally learned how to catch a key after... two yearsshow more

Multi-robot learning is getting a serious boost! 📚 Researchers... have extended Isaac Lab to train heterogeneous multi-agent robotic policies at scale. The new framework supports high-resolution physics, GPU-accelerated simulation, and both homogeneous and heterogeneous agents working together on coordination tasks. They benchmarked different approaches (MAPPO: Multi-Agent Proximal Policy Optimization and HAPPO: Heterogeneous Agent PPO) across six challenging scenarios and showed that large-scale multi-robot training is not only feasible, but efficient. It’s an important step for real-world robotic collaboration, where teams of robots need to coordinate, split tasks, adapt roles, and interact dynamically, not just operate as identical clones. The code is open-source, and it pushes Isaac Lab closer to what robotics actually needs: scalable, physics-driven environments where many different robots can learn to work together. Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →show more