A Compilation of Robots Falling Down at the DARPA Robotics Challenge

What people said

FabHK · 2018-01 · Recommendation

Moravec's paradox - stuff we thought is hard (chess, derivatives) is easy, while stuff we think is easy (face recognition, getting out of a car, opening a door) is really hard. [LINK] One of my favourite videos is this compilation of robots falling (failing) during the simplest tasks at the 2015 DARPA challenge: [VIDEO]

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marcusverus · 2025-03 · Reference

I remember thinking that the humanoid robotics revolution was imminent after seeing ASIMO walk around 2010[0], but after observing the slapstick comedy that was the DARPA Robotics Challenge around 2015[1], it seemed that we had actually made zero progress. But I haven't felt that way in years! My feeling at this point is that the best humanoid robots have, from a hardware perspective , surpassed the "minimally viable product" threshold. By this I mean that they are physically capable of completing enough tasks that would make them worthwhile a worthwhile product. They are physically capable of walking the dog, folding the laundry, picking up the living room, bringing in the groceries, etc. It's possible that there are reliability issues to address, but given that the newest generation of bots are fully electric, it's hard to imagine that this is a more difficult problem than those they've already solved. At this point, we're just waiting on the software to catch up. And surely this problem seems far more doable today than it did 20 years ago, given all the progress we've made in machine vision and machine learning! We'll know that the robotics revolution is truly imminent when the big players start pouring capital into development. Tesla has already joined the fray. I expect more will follow in the next few years. [0] [LINK] [1] [VIDEO]

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numpad0 · 2024-05 · Reference

It was always software. Humanoid robots could walk up and down stairs and use basic tools, in preprogrammed lab conditions and/or by manual teleoperations since 90s[1], and in theory autonomously since 2010s[2]. Nowadays they just can, thanks to NVIDIA CUDA, but grabbing objects is still sketchy[3]. 1: [LINK] 2: [VIDEO] 3: [LINK]

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