Prof. Dr. Wolfram Burgard
professor of computer science at the University of Freiburg and head of the research lab for Autonomous Intelligent Systems 
University of Freiburg, Germany
Profile
burgard [AT] informatik.uni-freiburg.de
 

Biography:

Prof. Dr. Wolfram Burgard is currently a professor of computer science at the University of Freiburg and head of the research lab for Autonomous Intelligent Systems. His areas of interest lie in the fields of artificial intelligence and mobile robots. His research mainly focuses on the development of robust and adaptive techniques for state estimation and control. Over the past years he has developed a series of innovative probabilistic techniques for robot navigation and control. They cover different aspects such as localization, map-building, SLAM, path-planning, exploration, and several other aspects. In his previous position from 1996 to 1999 at the University of Bonn he was head of the research lab for Autonomous Mobile Systems. He has published over 250 papers and articles in robotic and artificial intelligence conferences and journals. In 2005, he co-authored two books. Whereas the first one, entitled Principles of Robot Motion - Theory, Algorithms, and Implementations, is about sensor-based planning, stochastic planning, localization, mapping, and motion planning, the second one, entitled Probabilistic Robotics, covers robot perception and control in the face of uncertainty. In 2008, he became a Fellow of the European Coordinating Committee for Artificial Intelligence (ECCAI), and in 2009, a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). In 2009, he received the Gottfried Wilhelm Leibniz Prize, the most prestigious German research award. In 2010, he received an Advanced Grant of the European Research Council. Since 2012, he is the coordinator of the Cluster of Excellence BrainLinks-BrainTools funded by the German Research Foundation.

Speech : Probabilistic Techniques for Mobile Robot Navigation

 Probabilistic approaches have been discovered as one of the most powerful approaches to highly relevant problems in mobile robotics including perception and robot state estimation. Major challenges in the context of probabilistic algorithms for mobile robot navigation lie in the questions of how to deal with highly complex state estimation problems and how to control the robot so that it efficiently carries out its task.

 In this talk, I will present recently developed techniques for efficiently learning a map of an unknown environment with a mobile robot. I will also describe how this state estimation problem can be solved more effectively by actively controlling the robot. For all algorithms I will present experimental results that have been obtained with mobile robots in real-world environments including autonomous cars, logistics applications, and robots navigating in city environments.

Prof. S.K. Saha
Professor and Head of the Department of Mechanical Engineering at IIT Delhi 
Naren Gupta Chair Professor Programme for Autonomous Robotics & Dept. of Mech. Eng., IIT Delhi
Profile
saha [AT] mech.iitd.ac.in
 

Biography:

Prof. Subir Kumar Saha, Professor and Head of the Department of Mechanical Engineering at IIT Delhi is a 1983 mechanical engineering graduate from the RE College (Now NIT), Durgapur, India. He completed his M. Tech from IIT Kharagpur and Ph. D from McGill University, Canada. Upon completion of his Ph. D, he joined Toshiba Corporation’s R&D Center in Japan. After 4-years of work experience in Japan, he returned to India in 1995.

      He is actively engaged in teaching, research, and technology development. Prof. Saha recently completed the design and installation of an electrically-driven Six-DOF motion platform for an industry in India. Besides, he established the Mechatonics Laboratory at IIT Delhi in 2001, and contributed significantly to set-up an inter-disciplinary Programme for Autonomous Robotics at IIT Delhi in 2010.

 As recognition of his international contributions, Prof. Saha was awarded Humboldt Fellowship in 1999 by the AvH Foundation, Germany, and the Naren Gupta Chair Professorship at IIT Delhi in 2010. He has published a text book on “Introduction to Robotics” published by McGraw-Hill which is supported with a popular software RoboAnalyzer which he distributes free. He has also co-authored Dynamics of Tree-type Robotic Systems published by Springer in 2014.

 

Speech : Two Decades of DeNOC-based Modelling and Its Use in Robotics

The decoupled form of the Natural Orthogonal Complement (NOC) of the velocity constraint matrix of a mechanical system used in dynamic modeling is referred here as DeNOC. It has been proposed by the speaker first in 1995 during IEEE Conference on Robotics and Automation held in Nagoya, Japan. Initially, the concept was used for the development of recursive inverse and forward dynamics algorithms for serial-type mechanical systems, e.g., the industrial manipulators. Later, the methodology was extended to several systems with different topologies like parallel Stewart platform, serial flexible systems, and tree-type and closed-loop systems. A general-purpose software called Recursive Dynamic Simulator (ReDySIM) written in MATLAB, which is freely downloadable http://www.redysim.co.nr/. However, the original serial-chain algorithms were used in the educational software named RoboAnalyzer, also available free from www.roboanalyzer.com. Some of the advantages of the DeNOC-based formulation are:

1.     Analytical expressions of the terms appearing in the equations of motion, e.g., the Generalized Inertia Matrix (GIM).

2.     Physical interpretations of the above expressions, e.g., mass matrix of a composite- or articulated-body.

3.     Analytical decomposition of the GIM resulting into recursive, efficient, and numerically stable algorithms.

4.     With the introduction of ‘determinate’ and ‘indeterminate’ subsystems in a closed-loop system, generation of a very efficient inverse dynamics algorithm, etc.

The talk will revolve around how to formulate the dynamic equations of motion using the DeNOC, and its applications in several robotic systems like industrial robots, biped, quadruped, etc.

Prof. Bijan Shirinzadeh
Professor in the Department of Mechanical and Aerospace Engineering at Monash University 
Monash University, Australia
Profile
bijan.shirinzadeh [AT] monash.edu
 

Biography:

Professor Bijan Shirinzadeh received engineering qualifications: Bachelors Degrees in Mechanical and Aerospace Engineering, and Masters Degrees in Mechanical and Aerospace Engineering from the University of Michigan, Ann Arbor, Michigan, USA. He obtained PhD in Mechanical Engineering from University of Western Australia (UWA), Australia.  He is currently a full Professor in the Department of Mechanical and Aerospace Engineering at Monash University, Australia.  He is also the Director of Robotics & Mechatronics Research Laboratory (RMRL). He has been invited and keynote speaker at numerous international conferences. He has served on editorial boards of many high impact international journals and conferences.  His current research interests include advanced mechanisms and robotics; micro-nano manipulation mechanisms/systems; intelligent sensing and control; robotic-assisted minimally invasive surgery and micro-surgery; complex and autonomous systems including autonomous aerial vehicles (AAVs) and autonomous mobile robots; and manufacturing and automation sciences.

 

Speech : Micro/nano manipulation and flexure-based mechanisms research at RMRL

This presentation will focus on a number of research studies carried out in micro/nano manipulation at RMRL. These include research in the areas of design and analysis of parallel mechanisms and flexure-based mechanisms including mechanisms of various degrees of freedom; capacitive and laser-based sensing for trajectory tracking; and sensory-based control including robust control of manipulation mechanisms. Other research areas at RMRL will also be briefly described including robotic minimally invasive surgery; robotic fibre placement and multi-arm manipulation for automated fabrication of structural components. Further, hardware set-ups and experimental facilities will also be presented.

Dr. Mojtaba Ahmadi
Associate Professor, Department of Mechanical and Aerospace Engineering, and Director of Advanced Biomechatronics and Locomotion Laboratory 
Carleton University Ottawa, Ontario, Canada
Profile
Mojtaba.Ahmadi [AT] carleton.ca
 

Biography:

Dr. Ahmadi received his Bachelors in Mechanical Engineering from Sharif University in 1989, Master’s from Tehran University in 1992, and Ph.D. from McGill University (Center for Intelligent Machines) in 1998. As a postdoctoral fellow with the Electrical and Computer Engineering at Ecole Polytechnique de Montreal he conducted research on Telerobotics. He has then taken several senior industrial positions: with Opal-RT Technologies Inc. in Montreal, as the leader of the Advanced Robotics and Controls Group; with Quantum and Maxtor Corporations (Seagate today) in San Jose, California, as a senior servo engineer; and with the Institute for Aerospace Research of the National Research Council Canada in Ottawa, leading robotic design activities for a novel 8DOF robot for a high-speed wind tunnel facility. Dr. Ahmadi has been with the Department of Mechanical and Aerospace Engineering at Carleton University from 2005. He is a senior member of IEEE and a member of IEEE Robotics and Automation Society, as well as IEEE and Canadian Engineering in Medicine and Biology Societies. Dr. Ahmadi’s main interests are robot design for new applications, control systems, balance in walking for robots and human, and rehabilitation robotics. He has developed or contributed to various robotic projects including walking robots, mobile robots, robotic software, optimal trajectory planning for redundant robots, redundant manipulators design and control, rehabilitation robots for stroke and acute-care patients, balance aid devices, exoskeleton controllers, and flight simulation motion platforms. He is the founder and director of the Advanced Biomechatronics and Locomotion Laboratory (ABL) at Carleton University and a co-founder of GaitTronics Inc (together with his former students). Some of his research outcomes are already on the path for commercialization. For example, the mobility robotic system, Solowalk , has won a few awards from Ontario Brain Institute and Ontario Centres of Excellence and is being used in research at Ottawa Children’s Hospital with children with Cerebral Palsy and scheduled to be used  with Geriatric patients. Dr. Ahmadi’s research has been covered by several media or news outlets such as Canadian Broadcasting Corporation (CBC) and Discovery Channel. 

 

Speech : Rehabilitation Robotics: A Design Perspective

Robotics is emerging as a viable solution to numerous medical applications. It can improve the quality and efficiency of healthcare system, reduce trauma in surgery, assist patients in walking, or provide automation in medical research laboratories. Areas such as surgery, rehabilitation, independently living, and radiotherapy, are among the areas that widely use robotic systems. The recent advancement in underlying mechatronics technologies, including computers, sensors, actuators, or intelligent control, have increased the capability of robots in executing complex tasks, thus improving their chance of adoption by medical community. Nevertheless, designing robots is a complex multidisciplinary iterative process, where designers are required to have skills and communicate their designs in various disciplines, and work in a collaborative environment to bring innovative projects to completion. This talk, starts by a quick overview of robotic system evolution and multidisciplinary design process, with special emphasis given to biomedical robotics. The speaker will follow by discussing the current research in rehabilitation robotics at Carleton University’s Advanced Biomechatronics and Locomotion laboratory (ABL). The presenter’s research spans from aerospace robotics to stroke rehabilitation, early mobilization, and assistive devices. Major issues such as stability of interactive controllers, sensing, safety, and learning controllers, will be highlighted.