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0 pointsupbeat_general1y ago0 comments

The challenge here is not IK. Sure, you don’t need IK if your policy directly operates in joint space but this isn’t the motivation for doing RL.

IK to my knowledge is well known in every setting I am aware of.

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cloudbonsai1y ago· 1 in thread

> The challenge here is not IK.

No, a state-based RL research like this is essentially an IK problem. Given a goal position in the world frame, you need to find out the motor configuration to move your EEF to that goal position.

> IK to my knowledge is well known in every setting I am aware of.

Really? When I was working in this field, I've actually never seen anyone who used numerical/analytical IK methods on real robots.

Granted that I was not a Robotics engineer (I was a Deep Learning engineer in the team), but my impression at the time was that no practical IK solution was available for a robot with 8 DOF, let alone a 20 DOF robot like Shadow Hand.

upbeat_generalOP1y ago

Here’s the simple reason why this is not the case:

If you provide the 6DoF trajectory (+ gripper joints), a lot of robotics (manipulation in particular) is basically solved. The problem is, we don’t have these good trajectories.

Sure, joint space is commonly used for learned policies, but cartesian space isn’t uncommon either.

IK is really just not a major focus on the learning side of robotics because it’s not the problem. The problem is we don’t know what to do even at the slightly higher level.

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