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Yes, in a limited research experiment—but “20 minutes” means five minutes of human demonstration followed by 15 minutes of model adaptation, not teaching a general-purpose robot household work from scratch. Dobb-E was tested on a Stretch robot in a small set of real homes; researchers reported an 81% success rate across 109 tasks in their evaluation.
What Dobb-E is—and what the 20 minutes means
Dobb-E is an open research system designed to help a mobile robot learn household manipulation tasks, such as opening a drawer or putting an item in a bin. It is not a finished consumer robot or a general-purpose home assistant.
The paper describes a two-part workflow for a new task: a person demonstrates it for five minutes, then the system spends 15 minutes adapting its pretrained representation. That makes 20 minutes the combined demonstration-and-adaptation period—not 20 minutes of human instruction, and not a promise that any task can be learned in that time.
The researchers called the pretrained representation Home Pretrained Representations (HPR). To build its foundation, they collected 13 hours of demonstrations in 22 New York City homes. Volunteers used a device called The Stick, made from inexpensive components including an iPhone, to demonstrate everyday actions. The team then used a short, task-specific demonstration to adapt the system to a new task. The paper is available at On Bringing Robots Home.
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How the robot learned a task
- Collect demonstrations: People used The Stick to show actions such as opening and closing doors or drawers, switching lights, and putting a tissue in a bin.
- Build a household representation: The researchers trained HPR using the demonstrations collected across 22 homes.
- Demonstrate a new task: A user provided about five minutes of task-specific demonstration.
- Adapt and attempt the task: The model used a further 15 minutes to adapt before the robot tried the task.
For the robot trials, the team used Hello Robot’s Stretch, a mobile robot with a telescoping arm. Reporting on the project describes an iPhone mounted on the robot with a 3D-printed mount, mirroring the data-collection arrangement. The results therefore apply to this research setup, not to an arbitrary robot or phone.
What the home evaluation found
The paper reports experiments in 10 homes in New York City and surrounding areas, conducted over roughly 30 days. Across 109 household tasks, the researchers reported an overall success rate of 81%. That is the study’s result for its particular robot, tasks, homes, and evaluation—not a general reliability figure for household robots.
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Reported examples included pouring from a cup, opening blinds or a shower curtain, retrieving a board-game box from a shelf, and a short sequence involving placing a can in a recycling bag and lifting the bag. These examples show the range of actions attempted, but the reported overall rate should not be read as a guarantee that each task type—or an untested household job—will work reliably.
Where Dobb-E struggled
Real homes made the problem harder than a controlled demonstration. The paper highlights strong shadows and differences in the quality of demonstrations from non-expert users. Reporting also describes reflective surfaces, such as mirrors, confusing the robot.
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Some tasks were treated as too risky to attempt. One reported example was pulling a heavy object from a high position, such as opening a refrigerator door. That exclusion matters: the system’s measured performance does not cover every action a person might expect a home robot to try.
Is Dobb-E available to use at home?
The team released Dobb-E’s software stack, models, data, and hardware designs as open source to support research. That release does not make Dobb-E a ready-to-buy household product. The reported experiments used a Stretch robot, and the project sources do not establish a complete consumer setup, current hardware availability, or a price.
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A reacher-grabber helped inspire The Stick, but an ordinary grabber should not be assumed to work with Dobb-E. The sources do not identify an approved consumer kit or a compatible grabber model.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the result says about home robots
Dobb-E demonstrates a research approach for adapting a robot to household tasks with a short example, using demonstrations gathered from multiple homes as a starting point. Its 81% result is meaningful evidence of progress under the study’s conditions, while the failures and safety exclusions show why it is not yet equivalent to a dependable robot that can take on arbitrary chores.
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For context on the experiment and its reported examples, see MIT Technology Review Japan’s coverage of Dobb-E and the researchers’ paper.
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