Model Predictive Control for Real-Time Point-to-Point Trajectory Generation
(2019) In IEEE Transactions on Automation Science and Engineering 16(2). p.972-983- Abstract
The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We propose an approach based on model predictive control to solve the problem of point-to-point trajectory generation for a given final time. We discuss various choices of models, objective functions, and constraints for generating trajectories to transfer the state of the robot, while respecting physical limitations on the motion as well as fulfilling computational real-time requirements. Extensive simulation results illustrate the use of the approach, and experiments on an industrial robot in a challenging ball-catching task show the effectiveness of the approach also in demanding scenarios... (More)
The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We propose an approach based on model predictive control to solve the problem of point-to-point trajectory generation for a given final time. We discuss various choices of models, objective functions, and constraints for generating trajectories to transfer the state of the robot, while respecting physical limitations on the motion as well as fulfilling computational real-time requirements. Extensive simulation results illustrate the use of the approach, and experiments on an industrial robot in a challenging ball-catching task show the effectiveness of the approach also in demanding scenarios with real-time constraints on the computation.
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- author
- Ghazaei Ardakani, M. Mahdi LU ; Olofsson, Bjorn LU ; Robertsson, Anders LU and Johansson, Rolf LU
- organization
- publishing date
- 2019-04-06
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Computational modeling, Model predictive control (MPC), Optimization, Planning, real-time control, Real-time systems, Robot sensing systems, robotics, Trajectory, trajectory generation, trajectory optimization.
- in
- IEEE Transactions on Automation Science and Engineering
- volume
- 16
- issue
- 2
- pages
- 12 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85059007558
- ISSN
- 1545-5955
- DOI
- 10.1109/TASE.2018.2882764
- project
- RobotLab LTH
- PRACE
- SMErobotics
- language
- English
- LU publication?
- yes
- id
- 463e2205-4778-4198-9147-e1d33fd73b5e
- date added to LUP
- 2019-01-09 12:41:29
- date last changed
- 2023-04-24 22:01:12
@article{463e2205-4778-4198-9147-e1d33fd73b5e, abstract = {{<p>The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We propose an approach based on model predictive control to solve the problem of point-to-point trajectory generation for a given final time. We discuss various choices of models, objective functions, and constraints for generating trajectories to transfer the state of the robot, while respecting physical limitations on the motion as well as fulfilling computational real-time requirements. Extensive simulation results illustrate the use of the approach, and experiments on an industrial robot in a challenging ball-catching task show the effectiveness of the approach also in demanding scenarios with real-time constraints on the computation.</p>}}, author = {{Ghazaei Ardakani, M. Mahdi and Olofsson, Bjorn and Robertsson, Anders and Johansson, Rolf}}, issn = {{1545-5955}}, keywords = {{Computational modeling; Model predictive control (MPC); Optimization; Planning; real-time control; Real-time systems; Robot sensing systems; robotics; Trajectory; trajectory generation; trajectory optimization.}}, language = {{eng}}, month = {{04}}, number = {{2}}, pages = {{972--983}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Transactions on Automation Science and Engineering}}, title = {{Model Predictive Control for Real-Time Point-to-Point Trajectory Generation}}, url = {{http://dx.doi.org/10.1109/TASE.2018.2882764}}, doi = {{10.1109/TASE.2018.2882764}}, volume = {{16}}, year = {{2019}}, }