accuracy of gazebo simulation of arm vs real hardware

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What else is missing? In theory, what other factors complicates the simulation such that it cannot realistically match a real arm?*

Yes, I'm interested in this too. I would like an accurate dynamical model of the UR5 and other UR manipulators. But I don't yet know of a package or project that provides this kind of Gazebo "emulator" for a given robot system that includes both its accurate physical dynamics and captures the effects of any software delays (which might be appreciable and more important than subtle dynamic effects.)

To accurately simulate the dynamic response of the robot to command inputs you really need a model of all of its internal software/hardware/firmware controllers and you also need accurate dynamical models of its actuators.

On the subject of actuation, and a modeling approach to make a Gazebo model more realistic, I've been thinking about it but I think it needs to explicitly handle the actuators at least at a simple level.

I feel like there's an important concept put well here by Russ Tedrake:

http://manipulation.csail.mit.edu/rob...

One thing that might be surprising is that, despite the fact that the joint dynamics of a manipulator are highly coupled and state dependent, the PID gains for each joint are often chosen independently for each joint, and are constant (not gain-scheduled ).

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nearly all electric robots have fairly substantial gear reductions, often on the order of 100:1

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The "reflected inertia" of the arm at the motor is cut by the square of the gear ratio; or the "reflected inertia" of the motor at the arm is multiplied by the square of the gear ratio. This has interesting consequences -- as we move to the multi-link case, we will see that the inertia of the arm is a state-dependent function that captures the inertial coupling of the other joints in the manipulator. The motor inertia, on the other hand, is constant. For large gear ratios, this means the dynamics of the joint are less dependent on the nonlinear effects of joint position and velocity, making it relatively easy to tune constant feedback gains that perform well in all configurations

However, in short, if we're trying to use an effort controller, I think this means that we must have a simple model for how the arm's inertia tries to backdrive the motor inertias. Simply removing the active torque on the motor rotor does not set the joint torque to zero as viewed from the standpoint of the arm's inertia. Rather, setting the motor torque to zero will allow the rotor to freewheel, which actually dominates the overall inertia of the system. The actual effort seen by the "motor coils," which are what we would control with an effort joint interface, is very different from 1/N the joint torques from the manipulator dynamic equations.

I don't know if there's a good plugin framework for modeling actuator dynamics. Just having the gearbox (like ... (more)