Online Minimum-Jerk Trajectory Generation

Mahdi Ghazaei, Anders Robertsson, Rolf Johansson

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

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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.
Original languageEnglish
Title of host publicationProc. IMA Conf. Mathematics of Robotics
Publication statusPublished - 2015
Event2015 IMA Conference on Mathematics of Robotics - Oxford, United Kingdom
Duration: 2015 Sept 92015 Sept 11

Conference

Conference2015 IMA Conference on Mathematics of Robotics
Country/TerritoryUnited Kingdom
CityOxford
Period2015/09/092015/09/11

Bibliographical note

key=mahdi_imamr15
month=09

Subject classification (UKÄ)

  • Robotics and automation
  • Control Engineering

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