Startup Launches $1,688 Household Robot That Users Must Train Themselves
San Francisco startup Nori Robotics has sold out its first batch of A3 household robots, priced at $1,688, which owners train themselves to do chores rather than using it straight out of the box.
Nori Robotics, a Y Combinator-backed startup based in San Francisco, has launched the A3, a wheeled humanoid robot priced at $1,688 that the company says can help with household chores such as cooking, fetching items from the fridge, putting things away, loading the dishwasher, folding clothes and pouring ingredients.
The A3 has two arms fitted with claws that can grip objects and lift a couple of pounds each. It uses , a laser-based sensor that maps its surroundings, and cameras to navigate around a home, and a full charge keeps it running for up to eight hours. Nori says it has already sold out of its first batch of A3 units, more than 100 robots by one estimate.
Unlike a robot vacuum cleaner with a fixed set of abilities, the A3 is designed to be trained by its owner. Users can either write code for the robot or train it through a desktop app that simulates its movements, then package the results into 'skills' shared on an online marketplace. Nori says most of the robot's parts can be 3D printed and replaced by owners. In one demonstration, an A3 was shown turning pages of sheet music for a guitarist, showing its tasks are not limited to housework.
How the A3 will compare with rival household robots is not yet clear. Weave Robotics' Isaac 1, designed to fold clothes and make beds, costs $8,000 and is due to ship this fall, while 1X's bipedal Neo robot costs $20,000 and is expected next year. Because owners train the A3 themselves, Nori's approach may also mean the robot does not rely on , in which a human watches through a robot's cameras and remotely controls it.
Nori is building a second batch of 100 A3 units, which is expected to ship this fall to buyers willing to code or train the robot themselves.
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- Startup Launches $1,688 Household Robot That Users Must Train Themselves
