Please excuse the delayed reply. Thanks for the thoughtful question — really appreciate you taking a close look.

SpinStep is primarily a traversal framework, not a constraint solver. It operates on orientation-based logic, where each node has a quaternion, and traversal occurs by stepping into child nodes whose orientations fall within a defined angular threshold from the current orientation.

So instead of computing a path toward a goal state, SpinStep says: “Given my current rotation, which nearby nodes are rotationally reachable?” It’s useful when the orientation itself is the condition for progression, like in:

    Animation state machines

    Scene graph logic

    Robotics command routing

    or potentially drone formations

At the moment, it doesn’t compute transformation sequences to reach a goal state — i.e., it’s not a solver or planner. But I agree: the quaternion logic could be extended to track both rotational and translational progression, especially if you define formations as goal orientations + positions.

I'd be happy to open an issue on Ketu with a concrete idea — possibly describing how formation transitions could be modeled as quaternion steps through orientation "nodes," - each drone is a node - and how that might be used to route coordination logic.

Thanks again for the openness.