In this paper a sensor fusion scheme, called triangulation-based fusion (TBF) of sonar data, is presented. This algorithm delivers stable natural point landmarks, which appear in practically all indoor environments, i.e., vertical edges like door posts, table legs, and so forth. The landmark precision is in most cases within centimeters. The TBF algorithm is implemented as a voting scheme, which group sonar measurements that are likely to have hit a mutual object in the environment. The algorithm has low complexity and is sufficiently fast for most mobile robot applications. As a case study, we apply the TBF algorithm to robot pose tracking. The pose tracker is implemented as a classic extended Kalman filter, which use odometry readings for the prediction step and TBF data for measurement updates. The TBF data is matched to pre-recorded reference maps of landmarks in order to measure the robot pose. In corridors, complementary TBF data measurements from the walls are used to improve the orientation and position estimate. Experiments demonstrate that the pose tracker is robust enough for handling kilometer distances in a large scale indoor environment containing a sufficiently dense landmark set.

The Swedish and Finnish steel industry has a world-leading position in terms of efficient blast furnace operations with low CO2 emissions. This is a result of a successful development work carried out in the 1980s at LKAB (Luossavaara-Kiirunavaara Aktiebolag, mining company) and SSAB (steel company) followed by the closing of sinter plants and transition to 100% pellet operation at all of SSAB’s five blast furnaces. However, to further reduce CO2 emission in iron production, a new breakthrough technology is necessary. In 2016, SSAB teamed up with LKAB and Vattenfall AB (energy company) and launched a project aimed at investigating the feasibility of a hydrogen-based sponge iron production process with fossil-free electricity as the primary energy source: HYBRIT (Hydrogen Breakthrough Ironmaking Technology). A prefeasibility study was carried out in 2017, which concluded that the proposed process route is technically feasible and economically attractive for conditions in northern Sweden/Finland. A decision was made in February 2018 to build a pilot plant, and construction started in June 2018, with completion of the plant planned in summer 2020 followed by experimental campaigns the following years. Parallel with the pilot plant activities, a four-year research program was launched from the autumn of 2016 involving several research institutes and universities in Sweden to build knowledge and competence in several subject areas.

A recent multivariable laboratory process is presented together with its use in a graduate control course. The process is called the Quadruple-Tank Process and demonstrates a multivariable level control problem. The multivariable zero dynamics of the system can be made both minimum phase and nonminimum phase by simply changing a valve. This makes the Quadruple-Tank Process suitable for illustrating many concepts in linear and nonlinear multivariable control. In this paper some of these are described together with the basic setup of the process. Two computer exercises and one laboratory exercise have been developed as part of a course in multivariable and nonlinear control. These are detailed and some experience from the course is presented.

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