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I'm trying to control the toyota HSR with a higher level whole-body controller that computes velocities, but the robot only offers JointPositionInterfaces in it's ros_control HardwareInterface implementation.

As none of the standard ROS controllers accept a velocity and output a position my approach so far included to write an integrator as an ROS controller plugin that continuously integrates the velocity command into an position set point.

This works more or less, but some of the joints react with shaky movements to this, and none of the joints reach the desired velocity.

I would assume that i have to tune the integrator gain for each joint to track the desired velocities, but i'm wondering if there exist other methods to achieve this?

As the robot offers position and velocity feedback i was thinking about using the velocity error to improve the position set point calculation, but somehow do not think that a classical PID loop will work. Has anyone encountered a similar situation or knows some literature on that topic?

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As the robot offers position and velocity feedback i was thinking about using the velocity error to improve the position set point calculation, but somehow do not think that a classical PID loop will work.

Why do you think a PID won't help you out here?

I would try it, actually:

$$ q_c = \frac{\dot{q}_d}{s} + \text{PID} \left( \dot{q}_d - \dot{q} \right), $$

where $q_c$ is the position command, $\dot{q}_d$ is the desired velocity provided by the whole-body controller and $\dot{q}_d-\dot{q}$ is the velocity error, with $\dot{q}$ being the velocity feedback.

It's easy to recognize the feed-forward and the feedback terms in the law. $\text{PID}(\cdot)$ can be a simple integrator to begin with.

The control performance will depend on:

  • the quality of $\dot{q}_d$, hence of the whole-body controller.
  • the quality of $\dot{q}$ (you may think of replacing the standard velocity feedback offered by the system with a more accurate ad-hoc observer).

Assuming that the whole-body controller is, well, a controller and not a planner, you'll end up with two nested closed loops, the inner and the outer loop. The property of closed-loop systems to compensate for unmodelled quantities and impairments will help you track the desired velocity quite well.

Make sure that the inner loop (i.e., the feed-forward+PID) can run faster and be more reactive than the outer loop (i.e., the whole-body controller).

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