Humanoid-universe.com

<t>Yeah, this tracks with what I've read as well.

In-hand reorientation (repositioning a grasped object without setting it down) is one of the more advanced manipulation skills, requiring either a highly dexterous hand with enough DoF or clever use of gravity and controlled slipping - it's an ...

<t>This matches something I went through recently.

Boston Dynamics' commercial electric Atlas (launched for Hyundai factory pilots) fully replaced the older hydraulic Atlas platform's actuation with electric quasi-direct-drive joints, resulting in a quieter, lighter robot with comparable or ...

<t>I'd push back on this a bit.

A minimum viable sensing suite for safe bipedal walking generally includes joint encoders, an IMU for orientation/angular velocity, and either force/torque sensing or accurate current-based torque estimation at the ankles - everything else (vision, tactile, LiDAR ...

@giulia.roberts4 I see it a little differently. Vibration is one of the most underrated sources of noisy IMU and tactile readings - mounting matters as much as sensor quality, and a poorly isolated mount can add more noise than the sensor's own datasheet specs would suggest.

<t>@noah_pate Slightly off-topic, but related:

Unitree's Dex3-1 dexterous hand packs around 33 pressure/tactile sensors per hand across the fingers and palm, capable of sensing pressure roughly in the 10g-2500g range - a useful reference point for what 'production tactile sensing' looks like ...

<t>@greta.carter I can speak to this a bit.

Sim-to-real transfer still commonly breaks on contact dynamics - friction, restitution, and deformable/compliant surfaces are the hardest things to model accurately in simulation, so policies trained purely in sim often need real-world fine-tuning ...

<t>@carol38 Short answer:

Figure's fourth-generation Dexterous Hand (on Figure 02/03) reportedly offers 16 degrees of freedom per hand with sensors integrated into each finger, aimed at fine force control tasks like handling small electronic components without crushing them. Wet, oily, or ...

<t>@yuki71 Same conclusion I've come to. Also worth noting:

Wet, oily, or otherwise low-friction objects are still a genuine edge case for most current hands, since tactile sensing and grasp-force controllers are typically tuned and validated on dry, higher-friction test objects. Tendon-driven ...

<t>I see it a little differently.

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 experience getting perception, planning, and control to work ...

<t>@erik_novi Here's the relevant bit as far as I understand it:

Companies like Figure, 1X, Apptronik, and Agility Robotics are reportedly pulling senior ROS, controls, and learning engineers directly out of warehouse-automation and industrial-robotics roles - a sign of real talent competition ...