Professor Roger D Quinn
Biography: Roger D. Quinn is the Arthur P. Armington Professor of Engineering at Case Western Reserve University. He joined the Mechanical and Aerospace Engineering department in 1986 after receiving a PhD (1985) from Virginia Tech and M.S. (1983) and B.S. (1980) degrees from the University of Akron. He is a Fellow of ASME. He won the CWRU University Distinguished Research Award in 2019. He has directed CWRU Biologically Inspired Robotics since its inception in 1990 and graduated approximately 100 graduate students in the field, some of whom have reached leadership positions in industry and academics. His research, in collaboration with biologists including Profs. Roy Ritzmann and Hillel Chiel is devoted to the development of robots and control strategies based upon biological principles and modelling animal neuromechanical systems. Dozens of robots have been developed to either improve robot performance with biological principles or model animal systems to better understand them. He has authored more than 300 full-length publications and 9 patents on practical devices resulting from his work. His biology-engineering collaborative work on behaviour based distributed control, robot autonomy, human-machine interfacing, soft robots, and neural control systems have each earned awards.
Animal-inspired robots that crawl, walk, run, climb and fly and synthetic nervous systems for their control
Animal-inspired robots that crawl, walk, run, climb and fly and synthetic nervous systems for their control
Abstract
The goal of our research is to model animal locomotion systems using computational neuromechanics and then apply their designs and even their materials to robots to improve their mechanical designs, autonomous behaviours, and locomotion. This presentation summarizes our efforts over the last several decades and describes our recent work in more detail. We use bioinspiration or biomimicry depending on our specific goals. Using bioinspiration we have applied the fundamental principles of insect locomotion to develop robots using existing technologies and in a simplified manner. Their motor control is also simplified and the agility of these vehicles makes them suitable for some applications. This approach has been used to develop fast-running vehicles and a small fixed-wing vehicle called MALV (micro air and land vehicle) that flies lands and crawls. Using biomimicry, we are developing other robots and animal models including moth-like compliant, flapping wings that mimic those of the animal. We have developed a number of robots with multi-segmented legs mirroring those of animals. For example, Drosophibot is a dynamically scaled-up model of a fruit fly and Puppy is a model of a greyhound with artificial muscles. For these robots, we are developing synthetic nervous systems (SNS) for their control based upon animal neurobiology. We are also developing structurally soft worm-like robots, which crawl via peristaltic waves, for pipe inspection and, when made compact, within the body. Robots with a human in the loop for basic control decisions are limited in their movements in complex terrain because of sparse sensory data and limited communications. Some autonomy is essential for their agility. Insect neurobiology and behavioural experiments are being used to develop SNS navigation systems and decision-making strategies. Our autonomous snowploughs benefit from a distributed control architecture similar to that found in animals and will eventually implement an animal-inspired SNS brain. In still another approach, teaming with the bio-fabrication groups, we are developing small robots using organic materials.
Professor (RAS) Ivan L. Ermolov
Biography: Professor Ivan Ermolov is a Vice-director of Ishlinsky Institute for Problems in Mechanics of the Russian Academy of Sciences. Prof. Ivan Ermolov is a member of several Russian bodies of experts in Robotics and a Secretary of Scientific Council on Robotics and Mechatronics of Russian Academy of Sciences. He acts as a member of the Council on Strategic Planning and Prognosis of Russian Academy of Sciences. Starting 2018 he is Member of working group “Robotics” of IFAC. He has experience of participation of several European Framework Programmes’ projects and of bilateral international projects (E.g. HISMAR, AMETMAS-NoE, Royal Society etc). Prof. Ivan Ermolov teaches at Professor of Robotics of Moscow State Technological University “STANKIN”. His main research interests: robots’ autonomy, data fusion, perspective research in robotics.
| Ivan L. Ermolov Professor of Russian Academy of Sciences Vice-director of Ishlinsky Institute for Problems in Mechanics RAS Phone: +7 495 434 3547 E-mail: ermolov@ipmnet.ru |
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| Pr. Vernadskogo, 101-1, Moscow, 119526, Russia, phone: +7 495 434 0017, fax: +7 499 739 9531, e-mail: ipm@ipmnet.ru | |
Russian Robotics: State of Today, View for The Future
Prof. Ivan L. Ermolov
Ishlinsky Institute for Problems in Mechanics RAS, Scientific Council on Robotics and Mechatronics of Russian Academy of Sciences
Russia started its first experience in robotics in 1930s. But its highlight was in 1970s with first moon rovers – Lunokhod. Now Robotics is recognized as one of key technologies in Russia. National robotics program covers essential part of modern research areas of robotics. However now it’s a good point to target those research areas which will be crucial for robots of tomorrow.
This presentation will give an overview of the main research actors of Russian robotics and present Russian view for Robotics research for the future. Some questions of fundamental research in area of mechanics and control of robots, as well as specifics of robots’ applications will be discussed. These materials can be also used as guidelines for building international cooperation with Russian robotists.
Professor Yvan Baudoin
Biography: Professor Emeritus Yvan Baudoin is the former Head of the Department of Mechanical Engineering and former Executive Director of the Unmanned Vehicle Centre (http://mecatron.rma.ac.be) at the Belgian Royal Military Academy (RMA). He has extensive experience in coordinating large consortia at the international level such as the IARP working groups HU(manitarian)DEM(ining) (22 partners), RI(sky)S(urveillance)E(nvironment) (18 partners), the NATO/STO/ TG 175 focusing on intelligent assistance for autonomous vehicles (23 partners). He coordinated a EUREKA project (E!3517 – Towards a European Network of Environmental Engineering Sciences and Techniques) in which 164 SMEs and Academic Institutions from across Europe participated). He was also Co-Coordinator of the FP7-TIRAMISU (www.fp7-tiramisu.eu) project and Liaison Officer in the FP6 View-Finder project (more than 32 Fire-Fighting/Civil Protection Services in Europe). He now coordinates the Explosive – Robotics knowledge Centre of the International CBRNE Institute located in Belgium and also acts as vice-chair of the IMEKO TC17, organizing international symposia and workshop focusing on measurement and control of Robotics systems (ISMCR)
| YVAN BAUDOIN Professor EM Royal Military Academy ICI/EKC Manager Phone: +32 497 509244 E-mail: yvan.baudoin@ici-belgium.be |
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| Route de Sart-Dames-Avelines, 8A B 6210 Les Bons Villers (Frasnes-lez-Gosselies), Belgium Phone: + 32 71820840 Fax: +32 (0) 71/810635, E-mail: info@ici-belgium.be www.ici-belgium.be |
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Robotics Assistance to Predict, Prevent, Detect, Measure, Protect, Manage improvised CBE Risks
A natural or human-caused ‘disaster’ usually is a vast area where massive and diverse evidence must be located, collected and transferred for analysis to a distant reference laboratory. Every single detail may be crucial for the identification of the causes and/or the criminal actions of groups responsible for a potential risk caused by improvised chemical, biological and explosive devices. Nevertheless, the main difficulty is to determine which kind of evidence to look for. Detailed knowledge of similar events/contamination process could be helpful
Results of a threat analysis (prediction) will be useful (preparation of the plot, logistics, targeting, action, post-action steps – prevention). Cooperative multi-robot systems based on UAV and UGV equipped with modular sensors and intervention tools (detection, measurements) will carry out the screening, searching and collection of samples in the “hot zones” where the first responders could be exposed to dangerous and hazardous agents. Artificial intelligence techniques applied to the acquired data will contribute to improving detection and classification of evidentiary material and discrimination of mixed evidence, all of them critical for forensic investigations. Data fusion and artificial intelligence techniques will also be applied for predicting the dispersion patterns of some biological agents, providing in this way, a useful decision-making tool for first-responders.
In the aftermath of a BWA of a terrorist attack, the struck area is rather difficult to access by the first responders and LEAs and may have become hazardous, hostile or toxic, as (very partially) illustrated by the recent events in European Capitals. Establishing whether the ground can be entered safely by human beings is time-consuming. A major challenge is to quickly acquire and gather in situ data and forward information about the actual situation throughout the entire system: the Robotics assistance offers practical solutions to this problem.