MoveIt is currently primarily a kinematic motion planning framework - it plans for joint or end effector positions but not velocity or acceleration. However, MoveIt does utilize post-processing to time parameterize kinematic trajectories for velocity and acceleration values. Below we explain the settings and components involved in this part of MoveIt.
By default MoveIt sets the velocity and acceleration of a joint trajectory to the default allowed in the robot’s URDF or
joint_limits.yaml is generated from the Setup Assistant and is initially an exact copy of the values within the URDF. The user can then modify those values to be less than the original URDF values if special constraints are needed. Specific joint properties can be changed with the keys
max_position, min_position, max_velocity, max_acceleration. Joint limits can be turned on or off with the keys
The speed of a parameterized kinematic trajectory can also be modified during runtime as a fraction of the max velocity and acceleration set in the configuration values, as a value between 0-1. To change the speed on a per-motion plan basis, you can set the two scaling factors as described in MotionPlanRequest.msg. Spinboxes for setting both of those factors are also available in the MoveIt MotionPlanning RViz plugin.
Time Parameterization Algorithms¶
MoveIt can support different algorithms for post-processing a kinematic trajectory to add timestamps and velocity/acceleration values. Currently two are available by default in MoveIt: Iterative Parabolic Time Parameterization, and Iterative Spline Parameterization.
The Iterative Parabolic Time Parameterization algorithm is used by default in the Motion Planning Pipeline as a Planning Request Adapter as documented in this tutorial. Although the Iterative Parabolic Time Parameterization algorithm MoveIt uses has been used by hundreds of robots over the years, there is known bug with it.
The Iterative Spline Parameterization algorithm was recently merged into mainstream MoveIt in PR 382 to deal with these issues. While preliminary experiments are very promising, we are waiting for more feedback from the community before replacing the Iterative Parabolic Time Parameterization algorithm completely.
Open Source Feedback
See something that needs improvement? Please open a pull request on this GitHub page