Are legs a dead end compared to wheeled-torso designs for warehouses?

[emma_whit]

@smartinez Just to be precise about one thing: A genuinely underrated bottleneck is neither hardware nor pure ML - it's the unglamorous integration work of making perception, planning, and control agree with each other reliably for eight-hour shifts. The uncanny valley matters a lot less in a warehouse than in a living room - nobody cares if a picking robot looks a little stiff, but a home-companion robot with a slightly-off gait reads as unsettling fast.

[brian.campbell]

Thanks for laying this out, genuinely useful. Legs earn their keep specifically where the environment wasn't redesigned for robots - stairs, curbs, uneven yards, cluttered floors - which is a smaller slice of real-world tasks than the marketing suggests.

[jhansen]

Here's what I know on this: Open-source humanoid projects matter less for out-competing the well-funded players and more for keeping the barrier to entry low enough that new ideas and new people can actually get into the field.

[ivan22]

@jhansen Genuinely curious - Wheeled-torso designs solve 90% of warehouse and light-industrial tasks with far less complexity than a biped, which is exactly why so many 'humanoid' demos quietly have wheels under a skirt.

[sarah.santos3]

@ivan22 I'd take that specific number with a grain of salt, honestly. 'General purpose' in 2026 mostly means 'can be reprogrammed for a new task without new hardware,' not 'can walk into any environment and figure things out unsupervised.' Automotive plants ended up as the first serious proving ground for humanoids mostly because they already have structured environments, safety processes, and budget for automation - not because car assembly is uniquely suited to bipeds.

[mary.taylor6]

@sarah.santos3 Appreciate the detailed answer. Most flashy demo reels involve some amount of teleoperation, scripted sequencing, or cherry-picked takes - that's not necessarily dishonest, but it does mean the gap between 'demoed' and 'reliably autonomous in production' is still large. This whole thread is a good reminder how young this field still is.