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.
The robot learning laboratory is not confined to any specific robot system, but acts as a cooperation arena with the other laboratories of ROBOTNOR. Examples of laboratory activities include the development of a robot controlled camera system that learns how an operator would like to view his or her environment, and a robot arm that learns to grip and lift different objects.
Bestowing our machines with intelligence has been an ambitious goal for scientists since the birth […]
Often one sensor or one measurement principle can not capture all the information needed to […]
Machine vision is an essential part of most robotic system and is generally described as […]
Collision detection and avoidance are crucial components in any moving system that needs to interact […]
Vision sensors are necessary for the robots to understand and interact with their surroundings. Depending […]
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.
S. M. Albrektsen, S. A. Fjerdingen: “Safe Robot Learning by Energy Limitation”, in Proc. 5th Int. Conf. Intelligent Robotics and Applications (ICIRA 2012).
S. A. Fjerdingen, M. Bjerkeng, A. A. Transeth, E. Kyrkjebø, A. Røyrøy: “A Learning Camera Platform for Remote Operations with Industrial Manipulators”, in IFAC Workshop on Automatic Control in Offshore Oil and Gas Production, 2012.
S. A. Fjerdingen, E. Kyrkjebø: “Safe Reinforcement Learning for Continuous Spaces through Lyapunov-Constrained Behavior”, in Frontiers in Artificial Intelligence and Applications, 2011.
F. J. Marin, J. Casillas, M. Mucientes, A. A. Transeth, S. A. Fjerdingen, I. Schjølberg: “Learning Intelligent Controllers for Path-Following Skills on Snake-Like Robots”, in Lecture Notes in Computer Science, 2011.
S. A. Fjerdingen, E. Kyrkjebø, A. A. Transeth: “AUV Pipeline Following using Reinforcement Learning”, in Proceedings for the Joint Conference of ISR/ROBOTIK, 2010.