In this brief explainer Mehul Nariyawala argues that the field of indoor/home robotics has been developed “upside down.” He contrasts autonomous cars, which benefit from GPS and detailed maps, with indoor robots that started with the Roomba’s blind‑navigation approach. Although later models added more sensors, they still lack true spatial understanding of a home’s layout (kitchen vs. living‑room, left vs. right side of a couch). Nariyawala and his collaborator Namneet propose that fully autonomous indoor robots should be equipped with the same perception system humans use – specifically two RGB cameras paired with appropriate algorithms – to give robots a human‑like view of the indoor world.
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And very quickly, we came to this conclusion. And this was our conclusion that the entire field of indoor robotics, and specifically robots in homes, is built a bit upside down. It was like putting a cart before the horse. And the reason I say that is because even though self-driving cars requires all these sensors and vision and amazing algorithms, there are 2 things that self-driving cars have, which is Google Maps and GPS. So at least they know where they are located onto the road and which road and where road will be going. On the flip side, when it came to indoor robots, the analogy we realized is that in 2002, Roomba did a phenomenal job when there was no AI or technology available, did a phenomenal job of building a robot which had sort of this blindfold on it, would just bounce around and clean our home. That was a really great way to start robotics. But then along the way, more sensors got added. But those sensors weren't really converging into intelligence. A robot didn't really understand which part of the home they were, whether they were in the kitchen or dining area, right side of the living room or the left side— I mean, the right side of the couch or the left side of the couch. So we just realized that, look, if you're going to build fully autonomous indoor robots, then we should give it the same perception system that we as humans have, which is— Which is 2 RGB cameras and bunch of algorithm. And this is because, and this is the insight that Namneet and I have been operating on, that indoor world and specifically homes are built by humans for humans to take advantage or fit our perception system.
