In comparison to the Community Version, Ruckig Pro allows to generate more complex trajectories defined by intermediate waypoints. Therefore, Ruckig takes a list of positions as input and calculates a trajectory reaching them successively before moving to the target state. As this is a much harder problem than solving state-to-state motions (as the Community Version does), Ruckig Pro is not able to guarantee for a time-optimal trajectory. In fact, trajectory planning with intermediate waypoints is a non-convex problem and therefore NP-hard. However, Ruckig calculates much faster trajectories than other approaches, primarily due to the joint calculation of the path and time parametrization. On top, Ruckig is real-time capable and considers jerk-constraints.

In this regard, following information help to obtain robust and ideal optimization results:

1. Ruckig guarantees to output trajectories faster than a trajectory stopping at each intermediate waypoint (with zero velocity and acceleration).
2. Ruckig prefers as few waypoints as possible, both improving the (relative) trajectory duration as well as the computational performance. Note that the complexity of the calculation increases with the number of waypoints, in contrast to many other (time-parametrization) approaches that scale with the trajectory duration or path length. While Ruckig is tested with 50+ waypoints, we strongly recommend to limit the number of waypoints by a single-digit number.
3. Ruckig prefers waypoints that are not in straight-line positions. Please pre-process your list by state-of-the-art waypoint filtering methods (known from path parametrization) first. Fortunately, a straight line of dozens of waypoints is not a typical use-case seeking for near time-optimal trajectories.