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This is probably already possible, but I couldn't easily find this information in the docs. Nominally, for an N degree-of-freedom robot model, your Jacobian would be 6-by-N. But suppose we only want the Jacobian for a subset of those joints (or less importantly, even the degrees of freedom). Instead of computing the full Jacobian and then sub-slicing the resulting matrix, is there a way to more efficiently compute just the columns we care about and get a smaller matrix in the first place? |
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Yes, we can add this feature. @sea-bass Have you encountered any computational burden with Jacobian computation? Would you like a function to compute the Jacobian of a given set of indexes, for instance? |
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Yes, we can add this feature.
Currently,
computeJointJacobians
pre-compute all the quantities to extract the Jacobian for any joint or frame withgetJoinJacobian
orgetFrameJacobian
.computeJointJacobian(model,data,q,joint_id)
just returns the Jacobian for the givenjoint_id
.@sea-bass Have you encountered any computational burden with Jacobian computation?
I ask this question as normally, for robots such as humanoids, such operations are near the microseconds ;)
Would you like a function to compute the Jacobian of a given set of indexes, for instance?