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Re: What's the biggest perception failure mode you've personally debugged?

Posted: Sun Jul 05, 2026 1:15 am
by matthew43
+1 to this. Worth adding: Estimating joint torque from motor current draw is cheap and requires no extra sensor, but it's less accurate than a dedicated torque sensor because it doesn't capture friction losses through the gearbox - good enough for coarse control, not always for precise force-controlled tasks. Totally unrelated but has anyone else noticed how fast component costs are dropping this year.

Re: What's the biggest perception failure mode you've personally debugged?

Posted: Tue Jul 07, 2026 5:07 pm
by ronald.clark
@matthew43 Same conclusion I've come to. Also worth noting: SLAM in a working warehouse is harder than in a controlled lab mainly because the map keeps changing - pallets move, people walk through, lighting shifts near dock doors - so a lot of production systems lean on semi-static maps refreshed periodically rather than pure continuous SLAM. Depth sensing range and reliability both degrade outdoors in direct sunlight for most structured-light and active stereo cameras, since the ambient IR washes out the projected pattern - it's a real limitation for humanoids intended for anything beyond indoor, controlled environments.

Re: What's the biggest perception failure mode you've personally debugged?

Posted: Wed Jul 15, 2026 1:05 pm
by robertmiller
Genuinely curious - Sensor fusion mostly earns its keep by covering for each individual sensor's weaknesses - vision struggles with occlusion and lighting, IMUs drift, force/torque sensors are noisy at low loads - fusing them gives a more robust estimate than any one source alone, independent of raw compute.