Fields of competence
ROBOTNOR represents a unique synergy of academic and industrial expertise which allows us to counsel and comprehend a wide variety of tasks and projects. Our fields of competence are numerous and diverse.
Mainly aiming at automatic control systems within manufacturing and production, the integration of planning, scheduling, dynamic reconfiguration, sensor interaction, and device control is at focus. The system scopes of research and experimentation are at cell and shop-floor levels. The principal remedies used for development and experimentation are:
Together with, in some cases, specialized hardware for communication and proprietary code for application interfacing to certain devices, the entire control system development may be designed, implemented, and experimented or operated in a more flexible and general manner than a traditional approach. A traditional approach to cell or shop-floor level application development would employ a number of PLCs with limited computation capability, and integration of the application platforms of proprietary device controllers, which in their technology support tend to only focus on the device itself.
By employing more general and real-time responsive programming frameworks for control system development in manufacturing and production, we are able to perform fast development of new applications, develop better system designs and implementations, obtain a higher degree of reuse across unrelated applications or systems, and, most importantly, make room for highly advanced algorithms and artificial intelligence at all levels of the control systems.
Launched in 2009, this project aims to develop the next generation robotic technology for Norwegian […]
Mobile robot manipulators (mobile robots with one or more attached manipulator arms) will be prevalent […]
This project considers cost-effective monitoring for remote environmental friendly inspection and maintenance of offshore wind turbines.
Morten Lind and Amund Skavhaug. Using the blender game engine for real-time emulation of production devices. International Journal of Production Research, 50(22):6219-6235, 2012.
Morten Lind, Lars Tingelstad, and Johannes Schrimpf. Real-Time Robot Trajectory Generation with Python. In Workshop on Robot Motion Planning: Online, Reactive, and in Real-time. In IEEE/RSJ Int. conf. Intelligent Robots and Systems (IROS 2012), 2012.
Johannes Schrimpf, Morten Lind, and Geir Mathisen. Time-Analysis of a Real-Time Sensor-Servoing System using Line-of-Sight Path Tracking. In IEEE/RSJ Int. conf. Intelligent Robots and Systems (IROS 2011), pages 2861-2866, 2011.
Johannes Schrimpf, Lars Erik Wetterwald, and Morten Lind. Real-Time System Integration in a Multi-Robot Sewing Cell. In IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS 2012), 2012.