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Re: What's the current bottleneck in scaling manipulation training data collection?

Posted: Sun Aug 30, 2026 11:59 am
by matthew.yamamoto0
@nicole57 Counterpoint: Underactuated hands (fewer actuators than joints, using mechanical coupling to shape the grasp) are a reasonable engineering compromise for robust power grasps on a budget, but they generally can't do fine in-hand manipulation the way a fully actuated hand can.

Re: What's the current bottleneck in scaling manipulation training data collection?

Posted: Sun Aug 30, 2026 11:59 am
by timothy.roberts2
@matthew.yamamoto0 I dealt with almost this exact situation. 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.

Re: What's the current bottleneck in scaling manipulation training data collection?

Posted: Sun Aug 30, 2026 11:59 am
by mohammed.rossi
@timothy.roberts2 I dealt with almost this exact situation. 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.

Re: What's the current bottleneck in scaling manipulation training data collection?

Posted: Sun Aug 30, 2026 11:59 am
by rossi30
@mohammed.rossi From hands-on experience, Compliant wrists that absorb impact during a bad approach or misjudged contact reduce mechanical stress on the whole arm, which matters a lot for long-term reliability even though it's a less visible feature than the hand itself.

Re: What's the current bottleneck in scaling manipulation training data collection?

Posted: Sun Aug 30, 2026 11:59 am
by harmonicjen60
@rossi30 I'll believe the stronger version of that claim when it's independently verified. 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. Vision-based grasp confidence estimation (predicting success before attempting a grasp) and tactile-based confirmation (confirming after contact) are complementary rather than competing - vision helps you choose a grasp, tactile tells you if it actually worked.