Real-time control: It is the ability to manage and manipulate a system or process in a timely and responsive manner, typically with minimal delay between sensing and actuation. Applications of real-time control are widespread and can be found in various fields, including manufacturing, aerospace, automotive systems, medical devices, and robotics.
Sensor fusion: This is the process of combining data or information from multiple sensors to obtain a more accurate, reliable, and comprehensive understanding of a system or its environment than what could be achieved with individual sensors alone. Sensor fusion is widely used and we apply it in various fields, including robotics, autonomous vehicles, aerospace, industrial automation.
Motion planning: It involves the development of algorithms and techniques to generate feasible and collision-free trajectories for a robot or an autonomous system to move from one point to another in its environment. Motion planning is used in various fields and our applications include, autonomous vehicles (air, ground), and industrial automation.
Synchronized robots: It refers to a group (and even swarm) of robots operating in a coordinate and synchronized manner. The concept is often applied in various fields, such as robotics, automation, and manufacturing, to enhance efficiency, precision, and overall system performance.
Hybrid force/motion control: This is a control strategy that combines both force control and motion control in a robotic system. This approach allows a robot to simultaneously regulate its position and exert force in a way that is well-suited for applications where precise control over both aspects is crucial. Typical applications are in the field of manufacturing, material handling.
Manipulation learning: This is the process by which a robotic system acquires the ability to manipulate objects or interact with the environment through learning from experience/operator. Algorithms and techniques are developed to enable a robot to learn how to grasp, move, and manipulate objects effectively without relying on explicitly programmed instructions. Typical applications are in in field of manufacturing, service robotics.
Motion estimation: This is a process in computer vision and image processing that involves determining the movement or displacement of objects or features between consecutive frames of a video sequence. This is widely used in computer vision and robotics applications.
Target tracking: The primary goal of target tracking is to continuously estimate the position, size, and other relevant attributes of the target over time as it moves through a scene. Various tracking algorithms exist, ranging from traditional methods like mean-shift and Kalman filtering to more modern approaches utilizing deep learning techniques. Typical applications are in human-machine interaction, autonomous vehicles.
Mission planning: It deals with the creation of strategies or action sequences for execution by intelligent agents, autonomous robots, and unmanned vehicles. We focus on how to make it possible to achieve overall goals of autonomous missions while still being able to handle immediate events.
In ROBPLAN we will move the research front by developing methods for AI-based planning and acting - AI planning - to enable robust autonomous robot missions. We will demonstrate results on industrial use cases with mobile manipulators and Unmanned...
The primary objective of SAM is to optimize demanding industrial processes by developing advanced physical models and machine learning algorithms, and integrating new online sensors where real time data is currently limited or lacking.
The aim of TAPI (Towards Autonomy in Process Industries) is to move Norwegian land-based process industries towards more autonomous operations by exploring the intersection between machine learning (ML) and more traditional model-based control...
European consortium to standardise fuel cell modules for heavy duty applications: the “StasHH mission”
We will develop a set of wearable technologies and miniaturized sensors which protect and empower first responders, and their K9 companions, during response operations (natural calamities, e.g., earthquakes, and man-made attacks, e.g., terrorist...
Madshus is the oldest, still operating, producer of cross-country skis. The factory delivers advanced racing and entry level skis with regards to material quality, design, weight and defined ski properties.
The subsea industry is constantly pushing towards reduced costs and increased safety in subsea inspection, maintenance and repair operations. Therefore we have established the SEAVENTION project: Autonomous subsea intervention - empowered by people...
There are significant resources of wind power in areas where few people live, and which cannot be exploited due to a weak grid. A solution is to produce hydrogen and export it.
Development of methods and tools that will enable the online estimation and identification of moving objects and support the robot interaction and manipulation of such objects in real time.
Giantleap aims to increase lifetime and reliability of fuel cells in buses
SINTEF pushes the boundaries of autonomous drones. Mobile and autonomous sensor systems constitute a priority area at SINTEF. We offer a large range of relevant technologies and competence within this field for mobile and autonomous systems in the...
Autonomous mobile systems are capable of reasoning about and solving unstructured problems without the direct intervention of humans, and central to future exploitation of the ocean space.
Improving Lifetime of Fuel Cells by Smart Control and Prognostics
Testing wells simultaneously and with no production loss
The ESA wants its operations on other planets to have greater mobility and manoeuvrability. SINTEF researchers are looking into whether snake robots could be the answer.
Their brains are still no more advanced than that of a one-year-old, but scientists want robots to be as smart as teenagers – at least.
