Skip to main content

Scientists Discover Way to Send Information into Black Holes Without Using Energy

Post a Comment

Meet Aloha: The AI Housemaid Robot That Cooks, Cleans, and Learns Like a Human

Imagine a future where your house is cleaned, your meals are cooked, and your household tasks are completed—all by a smart robot. That future may be closer than you think. A team of researchers from Stanford University and Google DeepMind has introduced Mobile Aloha, a humanoid housekeeping robot that can cook shrimp, clean your kitchen, and even call and ride an elevator. This robot isn’t just smart—it’s mobile, teachable, and possibly the most promising step toward AI-powered domestic help.

Meet Aloha: The AI Housemaid Robot That Cooks, Cleans, and Learns Like a Human

What is Mobile Aloha?

Mobile Aloha is a humanoid robotic system designed to handle everyday household tasks. It builds upon the original Aloha system created by Google DeepMind, but with major upgrades, including full-body movement and mobility. The robot can be controlled remotely through whole-body teleoperation, which means operators can move both arms and its mobile base at the same time.

This makes Mobile Aloha different from typical robots that are usually fixed in one spot or limited to simple table-top tasks.

Why Was Aloha Created?

Modern robots are mostly used in factories or warehouses to do repetitive and productive tasks. But most of us need help at home with things that are non-productive yet time-consuming—like cleaning, cooking, or organizing. That’s where Aloha fits in.

The researchers behind Mobile Aloha wanted to create a robot that can assist humans with everyday household chores. They believe that robots should make life easier by taking care of these tasks, especially for people with disabilities, elderly individuals, or anyone with a busy lifestyle.

A Powerful Collaboration

Mobile Aloha is the result of a collaborative project between Stanford University, Google DeepMind, Meta, and the University of California, Berkeley. Each group brought in unique expertise in robotics, artificial intelligence, and mechanical engineering.

By combining their knowledge, they developed a system that is not only agile and intelligent but also easy to teach new tasks.

How Mobile Aloha Works

Mobile Aloha combines three important features:

  1. Mobility – It moves around your home smoothly.

  2. Bimanual Arms – It uses two robotic arms to interact with objects.

  3. Whole-Body Control – It can coordinate its arms and base to perform complex tasks.

The robot is operated using a special teleoperation interface, which lets a human trainer control the robot’s entire body in real time. This is useful during training, allowing Aloha to learn from human demonstrations.

It learns through a process called supervised behavior cloning, where it watches a human do a task (like cooking or cleaning) and then mimics that behavior. The robot can achieve up to 90% success rate in tasks like sautéing shrimp or storing kitchen items after being shown the task just 50 times.

Tasks Mobile Aloha Can Do

Mobile Aloha can already handle several complex tasks around the house, including:

  • Cooking and serving food (like shrimp)

  • Opening cabinets and putting away heavy pots

  • Calling and entering an elevator

  • Washing pans under a kitchen faucet

  • Organizing and tidying up items in different rooms

What’s exciting is that it does all of these tasks without being tied down to one spot. The robot can move freely and interact with real-world environments in a natural and efficient way.

Smart Hardware and Affordable Design

Mobile Aloha is not just smart; it's also cost-effective and practical. Here are some of its key hardware features:

  • Mobility Speed: It moves at a speed of about 1.42 meters per second.

  • Power System: A 1.26 kWh battery powers the robot. The battery weighs 14 kg and also balances the robot to prevent it from falling over.

  • Computation Unit: A regular laptop with a Nvidia 3070 Ti GPU (8GB VRAM) and Intel i7-12800H processor controls the robot.

  • Vision System: The robot uses three Logitech C922x RGB webcams to “see” its environment. Two are attached to the wrists, and one faces forward.

The robot collects real-time data from its arms, wheels, and cameras. This data helps it understand its surroundings and perform actions with greater precision.

Design That Works

The design of Mobile Aloha allows it to perform a wide range of movements and tasks:

  • It can reach vertically from 20 to 65 cm above the ground.

  • It can extend 100 cm beyond its base.

  • It can lift items weighing up to 1.5 kg (3.3 pounds).

  • It can pull with a force of up to 100 newtons, even at heights up to 1.5 meters.

These abilities allow the robot to interact with common household items like drawers, doors, utensils, and even electronics.

Learning from the Original Aloha

Mobile Aloha expands on the original Aloha system, which was focused mostly on tabletop teleoperation tasks. The mobile version adds much-needed movement, giving the robot freedom to roam around the house.

It still uses the same dataset from the original Aloha, meaning it can train using a large library of existing tasks. This is a major advantage over robots that require brand-new training for each environment or situation.

Affordable for the Future

Despite its advanced features, Mobile Aloha only costs about $32,000 to build. While that might seem expensive, it's relatively low for a multifunctional humanoid robot. Experts believe the cost will come down significantly once it goes into mass production.

Given the value it could bring—doing chores, cooking meals, helping the elderly—many people may see it as a worthwhile investment in the near future.

Limitations and Future Improvements

Although the system is impressive, there are still some limitations. For example:

  • It currently relies on a human to teleoperate and train it.

  • Its strength and grip may not match that of a human yet.

  • It may face difficulties in completely unfamiliar environments.

However, as AI technology and robotics hardware continue to improve, we can expect future versions of Aloha to become fully autonomous and much more capable.

Research Recognition and Availability

The researchers published their findings in Arxiv on January 4, although the results have not yet been peer-reviewed. Still, the robotics community is already excited about what this means for the future.

Mobile Aloha is not just a prototype—it is a vision of the future where robots can become true partners in our daily lives.

Conclusion: The Dawn of AI Housekeepers

With Mobile Aloha, the dream of having a robot that cleans your home, cooks your meals, and helps with daily tasks is becoming a reality. This advanced humanoid robot shows how far we’ve come in the field of AI, robotics, and machine learning.

Affordable, agile, and intelligent—Mobile Aloha may soon become the ultimate assistant for modern households. Whether you're a busy professional, a caregiver, or simply someone who dislikes doing dishes, your future housemaid might just be a robot.

Reference: Zipeng Fu, Tony Z. Zhao, Chelsea Finn, "Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation", Arxiv, 2025. https://arxiv.org/abs/2401.02117

Comments

Post a Comment

Popular

Scientists Discover Way to Send Information into Black Holes Without Using Energy

For years, scientists believed that adding even one qubit (a unit of quantum information) to a black hole needed energy. This was based on the idea that a black hole’s entropy must increase with more information, which means it must gain energy. But a new study by Jonah Kudler-Flam and Geoff Penington changes that thinking. They found that quantum information can be teleported into a black hole without adding energy or increasing entropy . This works through a process called black hole decoherence , where “soft” radiation — very low-energy signals — carry information into the black hole. In their method, the qubit enters the black hole while a new pair of entangled particles (like Hawking radiation) is created. This keeps the total information balanced, so there's no violation of the laws of physics. The energy cost only shows up when information is erased from the outside — these are called zerobits . According to Landauer’s principle, erasing information always needs energy. But ...
Post a Comment
Read more

How Planetary Movements Might Explain Sunspot Cycles and Solar Phenomena

Sunspots, dark patches on the Sun's surface, follow a cycle of increasing and decreasing activity every 11 years. For years, scientists have relied on the dynamo model to explain this cycle. According to this model, the Sun's magnetic field is generated by the movement of plasma and the Sun's rotation. However, this model does not fully explain why the sunspot cycle is sometimes unpredictable. Lauri Jetsu, a researcher, has proposed a new approach. Jetsu’s analysis, using a method called the Discrete Chi-square Method (DCM), suggests that planetary movements, especially those of Earth, Jupiter, and Mercury, play a key role in driving the sunspot cycle. His theory focuses on Flux Transfer Events (FTEs), where the magnetic fields of these planets interact with the Sun’s magnetic field. These interactions could create the sunspots and explain other solar phenomena like the Sun’s magnetic polarity reversing every 11 years. The Sun, our closest star, has been a subject of scient...
Post a Comment
Read more

Could Primordial Black Holes Have Formed from Aborted Phase Transitions?

Ai and colleagues propose a new way that primordial black holes (PBHs) could form in the early universe, using a mechanism that involves an "aborted phase transition." This takes place during the reheating phase after inflation, a period when the universe's temperature rises and then falls. During reheating, the universe is filled with a pressureless fluid called a reheaton. As the temperature rises to a maximum (Tmax), it surpasses the critical temperature needed for a phase transition, but not enough for bubbles to fully form and expand. These bubbles, which briefly nucleate as the temperature reaches Tmax, expand and then shrink as the temperature falls back below the critical level. When the bubbles shrink, they leave behind dense regions. These regions collect surrounding matter and eventually collapse into primordial black holes. The PBHs formed this way continue to grow in mass until the universe transitions into radiation domination. Primordial black holes (PBHs) ...
Post a Comment
Read more