IROS 2022poster1 citations

Jerk-continuous Online Trajectory Generation for Robot Manipulator with Arbitrary Initial State and Kinematic Constraints

Haoran Zhao, Nihal Abdurahiman, Nikhil Navkar, Julien Leclerc, Aaron T. Becker

Abstract

This work presents an online trajectory generation algorithm using a sinusoidal jerk profile. The generator takes initial acceleration, velocity and position as input, and plans a multi-segment trajectory to a goal position under jerk, acceleration, and velocity limits. By analyzing the critical constraints and conditions, the corresponding closed-form solution for the time factors and trajectory profiles are derived. The proposed algorithm was first derived in Mathematica and then converted into a C++ implementation. Finally, the algorithm was utilized and demonstrated in ROS & Gazebo using a UR3 robot. Both the Mathematica and C++ implementations can be accessed at https://github.com/Haoran-Zhao/Jerk-continuous-online-trajectory-generator-with-constraints.git

BibTeX
@inproceedings{iros2022_jerkcontinuouson,
  title = {Jerk-continuous Online Trajectory Generation for Robot Manipulator with Arbitrary Initial State and Kinematic Constraints},
  author = {Haoran Zhao and Nihal Abdurahiman and Nikhil Navkar and Julien Leclerc and Aaron T. Becker},
  booktitle = {IROS 2022},
  year = {2022}
}
Jerk-continuous Online Trajectory Generation for Robot Manipulator with Arbitrary Initial State and Kinematic Constraints · IROS 2022