IoT, AI, and Big Data in a pandemic era
Motion Control of Biomimetic Autonomous Underwater Vehicles:
Towards an Effective Diver/Robot Cooperation
Abstract: Biomimetic Autonomous underwater vehicles propose alternatives for
conventional propeller-driven underwater vehicles. Median and paired fin (MPF) locomotion is usually suggested as a viable alternative when high maneuverability and hovering capability is required. In fishes, such a propulsion mechanism usually means lower speeds (as opposed to body and caudal fin propulsion) but is advantageous when low speed and precision
maneuverability is desired. A particular type of MPF propulsion is sea turtle like 4-fin locomotion. Attempts to copy the locomotion of those agile and versatile reptiles reach back at least a decade with Turtle 2005 and Madeline. Other examples include Finnegan, the RobotTurtle and iRobot Transiphibian. Another line of development is represented by AQUA and AQUA2 four finned amphibian robots that are unique in the way the propellers are used
both for swimming and crawling in and out of water. Four-finned propulsion was also realized in some prototypes by deploying a scaffold structure actively controlled by shape memory alloy (SME) wires. U-CAT is an autonomous biomimetic underwater robot developed within a European Union 7th Framework project ARROWS (Archeological Robot Systems for the
World Seas). As opposed to the previous examples, four-finned design of this vehicle is motivated solely by the end-user requirements and environmental constraints of the tasks in this specifically shipwreck inspection. It should closely video-inspect underwater objects.
When interested to control of biomimetic autonomous underwater vehicles various challenges are to be considered (highly nonlinear dynamics, time-varying parameters, strong coupling between coordinates, underactuation, etc.).
This talk deals with motion control of Biomimetic autonomous underwater vehicles, with a special focus on the case study of U-CAT turtle-like biomimetic underwater robot.
All the proposed control solutions will be illustrated through different scenarios of real-time experiments in a swimming pool (controlled environment), as well as in open water (real operating conditions).
Energy harvesting in smart industrial machines: Generating the energy you need from the sources you know
Abstract: A smart system can be defined as a system incorporating sensing, actuation, control and communication, in order to adjust to or inform about the system’s context or own condition. Through technological advances, particularly in microelectronics, “smartness” has been demonstrated in a number of application domains, ranging from smart healthcare and smart homes, to smart cities and smart industries. To realize smartness on large scale, however, the energy supply to the necessary technologies is still a challenge. Batteries have been the go-to solution in cases where a fixed electrical infrastructure is infeasible or impossible. Batteries, however, have a limited energy capacity and lifetime, resulting in maintenance requirements that are typically undesirable at scale. Consequently, the conversion of ambient energy sources – commonly referred to as energy harvesting – is investigated as an alternative.
In this talk, an introduction as to what energy harvesting is, what it can be used for, and what challenges it faces, will be given. It will provide a holistic view, covering examples of energy sources to be exploited, conversion mechanisms to be utilized, and implementation aspects to be considered for system integration. During the talk, concrete cases of energy harvesting systems for smart industry applications will be explored in order to provide tangible examples. Moreover, open research challenges for energy harvesting and self-powered smart systems will be addressed, and an outlook on research trends given.
Application of deep learning in Arabic
speech processing and recognition
The presentation will give an overview of the recent advances in the applications of deep learning in language processing in general and speech recognition in particular. The talk will then provide a short review on the challenges facing Arabic Language and the recent research in Arabic language and Arabic speech. Finally we present our research activities along several Arabic language applications including, transcription of Arabic news, speech recognition of
Arabic dialects, Arabic language modeling using RNN, Arabic phoneme recognition, speech segmentation, automatic restoration of diacritical marks of Arabic text, Quran recitation, on-line Quran annotation, recognition of poem meters, and provide an overview of Arabic conversational agent.
The Planck Balance – calibration of E2 mass standards using the new definition
The Planck Balance (PB) is an electronic mass comparator, which allows the calibration of weights in a continuous range from 1 mg to 100 g using a fixed value of the Planck constant, h. It uses the physical approach of Kibble balances that allow the Planck constant to be derived from the mass.
Using the Planck-Balance no calibrated mass standards are required during the calibration of mass standards any longer, because all measurements are traceable via the electrical quantities to the Planck constant h, and to the meter and the second. This allows a new type of balance after the redefinition of
the SI-units on 20th of May 2019. In contrast to many scientific oriented developments of Kibble balances, the Planck Balance is focused on robust and daily use. The Planck Balance will allow relative measurement uncertainties comparable to the accuracies of class E2 mass standards, as specified in OIML Recommendation R 111-1. The Planck Balance is developed in a cooperation of the Physikalisch-Technische Bundesanstalt (PTB) and the Technische Universität Ilmenau in a project funded by the German Federal Ministry of Education and Research.