Comment by beau_g
2 days ago
On a freestanding humanoid robot, you have an inverse kinematic chain running all the way from the touch point to the ground, with many actuators in between, each of which to some degree squares the complexity of the problem. The parent article mentions a Fanuc or Kuka bot, which lets say is 6 axis - they are incredibly stiff/strong, in many cases many orders of magnitude stronger than they really need to be for the job they are tasked with, they do not move, modeling things like clashing with the environment/itself is much simpler because they are placed in 100% controlled environments - remove all of those qualifiers (weak robot because it needs to be light, dynamic environment, and count the DOF between the robots finger and it's ankles) and it gives a clearer picture than the article offers of why all this stuff is difficult. Can't take much of a divide and conquer approach like you can in other domains.
Inverse kinematics are piss easy.
When grasping an object you need to know the normal force on the contact point of the object and check that you're still in the friction cone.
This is hard, because you need to know the friction coefficient of the object and finger tip combination, you need to know the exact coordinates on the object you're putting that finger plus the orientation and graspable surfaces of the object and you have an imperfect model of the robot dynamics that doesn't account for friction or the dynamics of the manipulated objects.
Basically nothing is easy. You don't know anything about what you're manipulating.
>When grasping an object you need to know the normal force on the contact point of the object and check that you're still in the friction cone.
You don't. Certainly I do not need such information.
But that is what makes robotics hard, there is no easy answer as to how a human knows how to properly grasp an object.