Robot Control Overview: An Industrial Perspective
One key competence for robot manufacturers is robot control, defined as all the technologies needed to control the electromechanical system of an industrial robot. By means of modeling, identification, optimization, and model-based control it is possible to reduce robot cost, increase robot performa...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Norwegian Society of Automatic Control
2009-07-01
|
| Series: | Modeling, Identification and Control |
| Subjects: | |
| Online Access: | http://www.mic-journal.no/PDF/2009/MIC-2009-3-7.pdf |
| _version_ | 1828220380475555840 |
|---|---|
| author | T. Brogårdh |
| author_facet | T. Brogårdh |
| author_sort | T. Brogårdh |
| collection | DOAJ |
| description | One key competence for robot manufacturers is robot control, defined as all the technologies needed to control the electromechanical system of an industrial robot. By means of modeling, identification, optimization, and model-based control it is possible to reduce robot cost, increase robot performance, and solve requirements from new automation concepts and new application processes. Model-based control, including kinematics error compensation, optimal servo reference- and feed-forward generation, and servo design, tuning, and scheduling, has meant a breakthrough for the use of robots in industry. Relying on this breakthrough, new automation concepts such as high performance multi robot collaboration and human robot collaboration can be introduced. Robot manufacturers can build robots with more compliant components and mechanical structures without loosing performance and robots can be used also in applications with very high performance requirements, e.g., in assembly, machining, and laser cutting. In the future it is expected that the importance of sensor control will increase, both with respect to sensors in the robot structure to increase the control performance of the robot itself and sensors outside the robot related to the applications and the automation systems. In this connection sensor fusion and learning functionalities will be needed together with the robot control for easy and intuitive installation, programming, and maintenance of industrial robots. |
| first_indexed | 2024-04-12T16:26:28Z |
| format | Article |
| id | doaj.art-5e0594ae8c1345ab8e056c4b4d79ae79 |
| institution | Directory Open Access Journal |
| issn | 0332-7353 1890-1328 |
| language | English |
| last_indexed | 2024-04-12T16:26:28Z |
| publishDate | 2009-07-01 |
| publisher | Norwegian Society of Automatic Control |
| record_format | Article |
| series | Modeling, Identification and Control |
| spelling | doaj.art-5e0594ae8c1345ab8e056c4b4d79ae792022-12-22T03:25:22ZengNorwegian Society of Automatic ControlModeling, Identification and Control0332-73531890-13282009-07-0130316718010.4173/mic.2009.3.7Robot Control Overview: An Industrial PerspectiveT. BrogårdhOne key competence for robot manufacturers is robot control, defined as all the technologies needed to control the electromechanical system of an industrial robot. By means of modeling, identification, optimization, and model-based control it is possible to reduce robot cost, increase robot performance, and solve requirements from new automation concepts and new application processes. Model-based control, including kinematics error compensation, optimal servo reference- and feed-forward generation, and servo design, tuning, and scheduling, has meant a breakthrough for the use of robots in industry. Relying on this breakthrough, new automation concepts such as high performance multi robot collaboration and human robot collaboration can be introduced. Robot manufacturers can build robots with more compliant components and mechanical structures without loosing performance and robots can be used also in applications with very high performance requirements, e.g., in assembly, machining, and laser cutting. In the future it is expected that the importance of sensor control will increase, both with respect to sensors in the robot structure to increase the control performance of the robot itself and sensors outside the robot related to the applications and the automation systems. In this connection sensor fusion and learning functionalities will be needed together with the robot control for easy and intuitive installation, programming, and maintenance of industrial robots.http://www.mic-journal.no/PDF/2009/MIC-2009-3-7.pdfRoboticscontrolmodelslearningsensorsidentificationdiagnosisassembly |
| spellingShingle | T. Brogårdh Robot Control Overview: An Industrial Perspective Modeling, Identification and Control Robotics control models learning sensors identification diagnosis assembly |
| title | Robot Control Overview: An Industrial Perspective |
| title_full | Robot Control Overview: An Industrial Perspective |
| title_fullStr | Robot Control Overview: An Industrial Perspective |
| title_full_unstemmed | Robot Control Overview: An Industrial Perspective |
| title_short | Robot Control Overview: An Industrial Perspective |
| title_sort | robot control overview an industrial perspective |
| topic | Robotics control models learning sensors identification diagnosis assembly |
| url | http://www.mic-journal.no/PDF/2009/MIC-2009-3-7.pdf |
| work_keys_str_mv | AT tbrogardh robotcontroloverviewanindustrialperspective |