Humanoid-universe.com

<t>I'll believe the stronger version of that claim when it's independently verified.

How much ML background a controls role actually requires varies a lot by company and team - some whole-body control positions remain heavily classical-optimization-focused, while others increasingly expect ...

<t>That's the official framing, at least - reality tends to lag a bit.

Robotics engineers in the US were reportedly seeing $150k-$205k total comp at mid-level and $205k-$300k at senior level in 2026, with humanoid- and foundation-model-specialist roles clearing $280k-$475k - a meaningful premium ...

<t>@giulia.roberts4 That's the official framing, at least - reality tends to lag a bit.

A commonly cited skill gap in new-grad applicants is practical systems integration experience - many candidates are individually strong in ML or in mechanical design, but comparatively few have hands-on ...

<t>@carter42 Thanks for laying this out, genuinely useful.

IMU drift over time (bias instability) is usually the real culprit behind slowly diverging state estimates, not noise - it's typically handled with sensor fusion against other references (visual odometry, joint kinematics) rather than ...

<t>Slight correction, though the overall point stands:

Multi-camera calibration drifts over time from thermal expansion, vibration, and mechanical wear, which is why production systems typically run periodic recalibration routines rather than assuming a one-time factory calibration holds forever ...

<t>Slight correction, though the overall point stands:

Proprioception (the robot's sense of its own joint angles, velocities, and forces) tends to get less attention than flashy vision systems, even though a lot of balance and manipulation failures trace back to proprioceptive noise or ...

Counterpoint: Cable routing through a wrist joint with multiple degrees of freedom is a genuinely tricky mechanical design problem - tendons and wiring both need enough slack to avoid binding through the full range of motion without tangling or fraying over thousands of cycles.

<t>@amandawhite Small correction on one detail:

Building a scoped-down project first - a single leg, an arm, or a torso-only upper body - is a common and sensible way to learn the mechanical and control fundamentals before committing to the cost and complexity of a full bipedal platform ...

<t>@shill Slight correction, though the overall point stands:

Remote work remains genuinely limited for most hands-on humanoid hardware roles, given the need for physical access to robots and test environments, though software-only roles (simulation, perception algorithms, offline learning ...

<t>I'd frame this differently.

A strong, well-documented personal project (even a modest DIY build or a solid simulation-based RL project) reportedly carries real weight in hiring for this field, partly because the field is young enough that a demonstrated hands-on track record can meaningfully ...