Humanoid robots are designed to adapt to human workspaces, tackling repetitive or demanding tasks. However, creating general-purpose humanoid robots for real-world tasks and unpredictable environments is challenging. Each of these tasks often requires a dedicated AI model. Training these models from scratch for every new task and environment is a laborious process due to the need for vast task-specific data, high computational cost, and limited generalization.
NVIDIA Isaac GR00T helps tackle these challenges and accelerates general-purpose humanoid robot development by providing you with open-source SimReady data, simulation frameworks such as NVIDIA Isaac Sim and Isaac Lab, synthetic data blueprints, and pretrained foundation models. — Read More
Tag Archives: Robotics
China to host world’s first human-robot marathon as robotics drives national goals
For the first time, dozens of humanoid robots are expected to join a half-marathon to be held in the capital’s Daxing district in April, according to local authorities.
This comes as China ramps up efforts to develop artificial intelligence and robotics, to gain an edge in the tech rivalry with the US as well as combat the challenges of an ageing society and a falling birth rate.
Some 12,000 humans will take part in the coming race – and running alongside them on the 21km (13-mile) route will be robots from more than 20 companies, according to the administrative body of Beijing Economic-Technological Development Area, or E-Town.
Prizes will be offered for the top three runners. — Read More
It’s Surprisingly Easy to Jailbreak LLM-Driven Robots
AI chatbots such as ChatGPT and other applications powered by large language models (LLMs) have exploded in popularity, leading a number of companies to explore LLM-driven robots. However, a new study now reveals an automated way to hack into such machines with 100 percent success. By circumventing safety guardrails, researchers could manipulate self-driving systems into colliding with pedestrians and robot dogs into hunting for harmful places to detonate bombs.
Essentially, LLMs are supercharged versions of the autocomplete feature that smartphones use to predict the rest of a word that a person is typing. LLMs trained to analyze to text, images, and audio can make personalized travel recommendations, devise recipes from a picture of a refrigerator’s contents, and help generate websites.
The extraordinary ability of LLMs to process text has spurred a number of companies to use the AI systems to help control robots through voice commands, translating prompts from users into code the robots can run. For instance, Boston Dynamics’ robot dog Spot, now integrated with OpenAI’s ChatGPT, can act as a tour guide. Figure’s humanoid robots and Unitree’s Go2 robot dog are similarly equipped with ChatGPT.
However, a group of scientists has recently identified a host of security vulnerabilities for LLMs. So-called jailbreaking attacks discover ways to develop prompts that can bypass LLM safeguards and fool the AI systems into generating unwanted content, such as instructions for building bombs, recipes for synthesizing illegal drugs, and guides for defrauding charities. — Read More
Inside Google’s 7-Year Mission to Give AI a Robot Body
It was early January 2016, and I had just joined Google X, Alphabet’s secret innovation lab. My job: help figure out what to do with the employees and technology left over from nine robot companies that Google had acquired. People were confused. Andy “the father of Android” Rubin, who had previously been in charge, had suddenly left. Larry Page and Sergey Brin kept trying to offer guidance and direction during occasional flybys in their “spare time.” Astro Teller, the head of Google X, had agreed a few months earlier to bring all the robot people into the lab, affectionately referred to as the moonshot factory.
I signed up because Astro had convinced me that Google X—or simply X, as we would come to call it—would be different from other corporate innovation labs. The founders were committed to thinking exceptionally big, and they had the so-called “patient capital” to make things happen. After a career of starting and selling several tech companies, this felt right to me. X seemed like the kind of thing that Google ought to be doing. I knew from firsthand experience how hard it was to build a company that, in Steve Jobs’ famous words, could put a dent in the universe, and I believed that Google was the right place to make certain big bets. AI-powered robots, the ones that will live and work alongside us one day, was one such audacious bet.
Eight and a half years later—and 18 months after Google decided to discontinue its largest bet in robotics and AI—it seems as if a new robotics startup pops up every week. I am more convinced than ever that the robots need to come. Yet I have concerns that Silicon Valley, with its focus on “minimum viable products” and VCs’ general aversion to investing in hardware, will be patient enough to win the global race to give AI a robot body. And much of the money that is being invested is focusing on the wrong things. Here is why. — Read More
OpenAI’s Newest AI Humanoid Robot – Figure 02 – Just Stunned the Robotics World!
Perforation-type anchors inspired by skin ligament for robotic face covered with living skin
Skin equivalent, a living skin model composed of cells and extracellular matrix, possesses the potential to be an ideal covering material for robots due to its biological functionalities. To employ skin equivalents as covering materials for robots, a secure method for attaching them to the underlying structure is required. In this study, we develop and characterize perforation-type anchors inspired by the structure of skin ligaments as a technique to effectively adhere skin equivalents to robotic surfaces. To showcase the versatility of perforation-type anchors in three-dimensional (3D) coverage applications, we cover a 3D facial mold with intricate surface structure with skin equivalent using perforation-type anchors. Furthermore, we construct a robotic face covered with dermis equivalent, capable of expressing smiles, with actuation through perforation-type anchors. With the above results, this research introduces an approach to adhere and actuate skin equivalents with perforation-type anchors, potentially contributing to advancements in biohybrid robotics. — Read More
Meet the humanoids: 8 robots ready to revolutionize work
In 2015, Klaus Schwab, founder of the World Economic Forum, asserted that we were on the brink of a “Fourth Industrial Revolution,” one powered by a fusion of technologies, such as advanced robotics, artificial intelligence, and the Internet of Things.
“[This revolution] will fundamentally alter the way we live, work, and relate to one another,” wrote Schwab in an essay published in Foreign Affairs. “In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before.”
The recent surge of developments in AI and robotics — and their deployment into the workforce — seems right in line with his predictions, although almost ten years on. — Read More
China’s S1 robot impresses with its ‘human-like’ speed and precision
The era of humanoid robots seems to flourish, with new models being developed and trained at exceptional speeds.
Another Chinese firm making advanced strides in this realm is Astribot. The Senzhen-based subsidiary of Stardust Intelligence is a robotics firm focused on developing AI robot assistants.
In a video released by the firm, its humanoid S1 is seen doing household tasks at an unprecedented pace, which marks a significant advancement for a robot. — Read More
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Maybe I don’t want a Rosey the Robot after all
Boston Dynamics’ latest — deliberately creepy? — humanoid robot has me rethinking my smart home robot dreams.
As a child of the 1980s, my perception of the smart home has been dominated by the idea that one day, we will all have Rosey the Robot-style robots roaming our homes — dusting the mantelpiece, preparing dinner, and unloading the dishwasher. (That last one is a must; we were smart enough to come up with a robot to wash our dishes; can’t we please come up with one that can also unload them?)
However, after seeing Boston Dynamics’ latest droid, Atlas, unveiled this week, my childhood dreams are fast turning into a smart home nightmare. While The Jetsons’ robot housekeeper had a steely charm, accentuated by its frilly apron, the closer we come to having humanoid robots in our home, the more terrifying it appears they will be. Not so much because of how they look — I could see Atlas in an apron — but more because of what they represent. — Read More
Is robotics about to have its own ChatGPT moment?
Researchers are using generative AI and other techniques to teach robots new skills—including tasks they could perform in homes.
… What separates this new crop of robots is their software. Instead of the traditional painstaking planning and training, roboticists have started using deep learning and neural networks to create systems that learn from their environment on the go and adjust their behavior accordingly. At the same time, new, cheaper hardware, such as off-the-shelf components and robots like Stretch, is making this sort of experimentation more accessible.
Broadly speaking, there are two popular ways researchers are using AI to train robots: reinforcement learning, an AI technique that allows systems to improve through trial and error, to get robots to adapt their movements in new environments, and imitation learning, models learn to perform tasks by, for example, imitating the actions of a human teleoperating a robot or using a VR headset to collect data on a robot. — Read More
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