facebookresearch / differentiable-robot-model
We are implementing differentiable models of robot manipulators, which allows us to learn typically assumed to be known models of robots for control and motion planning.
Summary
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| Main Code: 6,820 LOC (24 files) = URDF (75%) + PY (24%) | |||
| Duplication: 60% | |||
| File Size: 0% long (>1000 LOC), 10% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 59% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 92% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (9 components) | ||
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1 year, 3 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2021-10-19
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