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Online Minimum-Jerk Trajectory Generation

Ghazaei, Mahdi LU ; Robertsson, Anders LU and Johansson, Rolf LU (2015) 2015 IMA Conference on Mathematics of Robotics
Abstract
Robotic trajectory generation is reformulated as a controller design problem. For minimum-jerk trajectories, an optimal controller using the Hamilton-Jacobi-Bellman equation is derived. The controller instantaneously updates the trajectory in a closed-loop system as a result of the changes in the reference signal. The resulting trajectories coincide with piece-wise fifth-order polynomial trajectories for piece-wise constant target states. Since having hard constraints on the final time poses certain robustness issues, a smooth transition between the finite-horizon and an infinite-horizon problem is developed. This enables to switch softly to a tracking mode when a moving target is reached.
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Contribution to conference
publication status
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conference name
2015 IMA Conference on Mathematics of Robotics
project
LCCC
language
English
LU publication?
yes
id
c9bcbbd4-f304-454e-8f33-9a78c4a97f1a (old id 7856574)
date added to LUP
2015-09-07 09:53:51
date last changed
2016-04-16 11:24:06
@misc{c9bcbbd4-f304-454e-8f33-9a78c4a97f1a,
  abstract     = {Robotic trajectory generation is reformulated as a controller design problem. For minimum-jerk trajectories, an optimal controller using the Hamilton-Jacobi-Bellman equation is derived. The controller instantaneously updates the trajectory in a closed-loop system as a result of the changes in the reference signal. The resulting trajectories coincide with piece-wise fifth-order polynomial trajectories for piece-wise constant target states. Since having hard constraints on the final time poses certain robustness issues, a smooth transition between the finite-horizon and an infinite-horizon problem is developed. This enables to switch softly to a tracking mode when a moving target is reached.},
  author       = {Ghazaei, Mahdi and Robertsson, Anders and Johansson, Rolf},
  language     = {eng},
  title        = {Online Minimum-Jerk Trajectory Generation},
  year         = {2015},
}