Under-Actuation Mechanism for Shadow Hand #2300
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JYChen18
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Hi @JYChen18, we actually have a model that reproduces the real world behavior, it's actually from the OpenAI paper from 2019. I can try to find some time to create a version in Menagerie in the next couple weeks. |
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Intro
Hi!
I am a graduate student at Peking University, I use MuJoCo for my research on dexterous grasping and manipulation.
My setup
MuJoCo 3.2.6, python, Linux Ubuntu 20.04
My question
The under-actuation mechanism in the MuJoCo simulation differs significantly from that of the real product, contributing to a large sim2real gap, especially in precise grasping and manipulation tasks.
In the simulation, the motion of FFJ1 and FFJ2 is always identical, with each joint receiving roughly half of the combined control signal FFJ0, mediated by the tendon.
However, on the real Shadow Hand, the behavior is different: when the control signal FFJ0 is less than 90 degrees, FFJ1 remains nearly stable (almost equal to 0) while FFJ2 increases from 0 to 90. Once FFJ0 exceeds 90 degrees, FFJ1 begins to increase from 0 to 90 and FFJ2 stops moving at 90 degrees.
Given that the real product’s behavior cannot be altered, is there a mechanism in MuJoCo that can better approximate this phenomenon to reduce the sim2real gap?
Minimal model and/or code that explain my question
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