Hi Johannes
You mean me, _Mark, not Marek, right?
(same name, different language, different person ;-)
Up to the Advanced Motion Control project, OpenPnP was only able to move the machine in single straight segments, each segment made a full stop and OpenPnP was waiting (and the task blocked) until completion. The waiting also involved a USB ping-pong or even parsing for a state (TinyG), adding some delays on slow connections.
On the other hand, this system is very simple, you never have to
think much about the machine state. Either OpenPnP is blocked and
the machine moving, or the other way around. That's why I needed
to make the migration backwards compatible. By default the
configuration remains the same. Simple but slow.
That why there is the Allow continuous motion switch.
https://github.com/openpnp/openpnp/wiki/Motion-Planner#motion-planner
You have to actively enable it after the upgrade, to
signal you are ready to face the consequences.
Now OpenPnP can generate whole motion sequences and the send them all at once. Furthermore, if code emits moveTo() commands, it will not wait around for completion. This will only be done when functionally needed, i.e. the code must tell when it needs completion:
https://github.com/openpnp/openpnp/wiki/Motion-Planner#motion-path-planning
OpenPnP will currently automatically complete Motion Paths in these cases:
So to go back to your test case:
You need to enable Allow continuous motion. Then it
should work.

It does physically move right on my TinyG. No
deceleration between segments. Same with Jogging many fast
clicks.
BUT: my planner can't predict
continuous straight S-Curves right. It just does not cover that,
algorithmically. So the Diagnostics will be wrong, showing
deceleration and too much time planned:

However, such moves never happen in OpenPnP, AFAIK. So this is mostly irrelevant.
You can set it to Full3rdOrderControl. Prediction does
still not match in time, but in shape:


_Mark
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