Biography:

Received his BSc in mechanical engineering and also pure mathematics from Sharif University of Technology, Tehran, Iran in 2002. He received his MSc and PhD in Mechanical Engineering, in the field of dynamics and control, from the same University in 2004 and 2008, respectively. At present, he is a professor in mechanical engineering at Sharif University of Technology. His research interests include dynamical systems, control theory and stochastic systems. He has led numerous industrial research projects in the fields of automation, control and navigation. One of his recent areas of interest is inertial sensor based motion capturing systems; and he has supervised several master and doctoral projects in this field.

Speech: Inertial-sensor-based motion capture using nonlinear filtering methods

Human motion tracking has many applications in biomedical and industrial services. Motion analysis in sport science, virtual reality production in the gaming and entertainment industry, rehabilitation and medical industry are areas in which motion capture systems have played an important role. Motion capture systems have different types from camera-based systems to inertial sensor (accelerators-gyros) based wearable ones. Optical systems are usually very expensive and have functions limited to indoor studios. In contrast, low-cost inertial/magnetic sensors can be used in outdoor and large environments to obtain the orientation of the human body segments in human motion capture systems. In this speech, at first a historical review of various methods of motion capture systems is presented. Then quaternion-based nonlinear filter algorithms to combine inertial/magnetic sensors measurements for tracking of human body movements are discussed. In order to have a better estimation of the orientation of the body segments, constraint equations are developed based on the relative velocity and position of the body joints with respect to the inertial sensors attached to the segments. Also to compensate for fast body motions, the measurement covariance matrix is updated in such a way that the filter uses gyros when large accelerations are involved. To improve the accuracy and reliability of system, it is discussed that how the installation location of the sensors on the body segment can be estimated as well as the sensor non-idealities such as misalignment, non-orthogonality and biases. Also an algorithm for data fusion of the inertial sensor-based motion capture and the Kinect, which is also a low-cost camera-based system utilized for motion analysis, is presented. To this end, a new measurement model of the fusion is obtained that can compensate for the inertial sensors drift problem in high dynamic motions and also joints occlusion in the Kinect. The proposed algorithms are evaluated experimentally by an optical tracking system as the ground truth reference. The results show the effectiveness and good performances of the proposed algorithms.

Biography:

Moharam Habibnejad Korayem received his BSc (Hon) and MSc in Mechanical Engineering from the Amirkabir University of Technology in 1985 and 1987, respectively. He has obtained his PhD degree in mechanical engineering from the University of Wollongong, Australia, in 1994. He is a Professor in mechanical engineering at the Iran University of Science and Technology. He has been involved with teaching and research activities in the robotics areas at the Iran University of Science and Technology for the last 25 years. His research interests include dynamics of elastic mechanical manipulators, trajectory optimization, symbolic modeling, robotic multimedia software, mobile robots, industrial robotics standard, robot vision, soccer robot, and the analysis of mechanical manipulator with maximum load carrying capacity. He has published more than 670 papers in international journals and conferences in the robotic area.

Speech: Recent Advances in Flexible Manipulators and Applications

Utilization of flexible link manipulators has been rising recently due to their wide range of applications in industry, medicine, aerospace, instrumentation, satellites and industrial automation. Such manipulators are replacing rigid links with larger dimensions and more weight in various industries. This talk will present the dynamic model of a flexible manipulator composed of N elastic links and robot actuators for which structural vibration is considered in order to determine dynamic load carrying capacity (DLCC). In view of the concurrent linear and rotary motions of the link caused by revolute-prismatic joints, the interaction of joint’s structural vibration and link fluctuation is taken as an effective model parameter. To model the expressed hub oscillation with respect to the link, the assumed modes method and mode shapes of Euler-Bernoulli beam with independent generalized modal coordinate with respect to the link are employed. The obtained equations are simultaneously solved in the coupled form and the simulation results are compared with a similar experimental setup, indicating that the flexible manipulator model with elastic link, hub and joints yields satisfactory results. Finally, several related projects which are conducted in the IUST Robotics Laboratory will be presented.

Biography:

Hossein Rouhani is an assistant professor in the Department of Mechanical Engineering at the University of Alberta since 2015. He received a PhD degree in Biotechnology and Bioengineering from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 2010 where he was a postdoctoral fellow in 2011. Dr. Rouhani was then a Postdoctoral Fellow in the Institute of Biomaterials and Biomedical Engineering at the University of Toronto from 2012 to 2015. Dr. Rouhani is the director of Neuromuscular Control and Biomechanics Laboratory at the University of Alberta, and his fields of research are musculoskeletal biomechanics, biomedical instrumentation design, and development of wearable neuro-rehabilitative technologies. Within his translational research program, Dr. Rouhani has had several collaborative research projects with university hospitals, such as University Hospital of Lausanne, Toronto Rehabilitation Institute, and Glenrose Rehabilitation Hospital. Dr. Rouhani is a recipient of two postdoctoral fellowship awards from the Swiss National Science Foundation. He is also an associate editor of the IEEE Canadian Journal of Electrical and Computer Engineering, and Frontiers in Sports and Active Living, and a co-chair of Alberta Biomedical Engineering Conference. He is also the congress chair for 2021 International Congress of the Canadian Society of Mechanical Engineers (CSME) and the vice-chair of the CSME technical committee for Biomechanics and Biomedical Engineering.

Speech: Closed-loop controlled neural prosthesis:Reverse engineered human body to enable human

People with disability represent the biggest minority in the world. Disabilities constrain physical activities, independence, and quality of life. Conditions such as brain and spinal cord injury, and multiple sclerosis may lead to long-term disabilities that require healthcare services. The worldwide increase in life expectancy and population growth challenge the healthcare system in the next decades due to a shortage of healthcare resources. Solutions to reduce the disability and dependence are needed to alleviate such challenges. Neural prostheses are devices that can substitute the impaired neuromuscular system and restore motor functions. A majority of the developed and clinically implemented neural prostheses are open-loop systems unable to adjust their function in response to perturbations or change in the environmental or physiological conditions. Closed-loop controlled neural prostheses are suggested to address this short-coming. In this talk, we present a bio-inspired approach to develop closed-loop controlled neural prostheses, as the reverse engineered neuromuscular system. We will discuss modelling the function of different components of the neuromuscular control system, assessment of the body motion in real-time and artificial activation of the skeletal muscles to restore motor functions. Details of the development and experimental implementation of a neural prosthesis for standing balance will be presented as an example of our proposed approach.

Biography:

Saeed Behzadipour received his BSc and MSc in Mechanical Engineering from Sharif University of Technology in 1998 and 2000, respectively. He received his PhD in Mechanical engineering from University of Waterloo, in 2005. He was an assistant professor in Mechanical Engineering in University of Alberta, Canada from 2005 to 2011. He is an associate professor of Mechanical Engineering at Sharif University of Technology and director of Djawad Movafaghian Research Center in Neurorehabilitation. His research interests include rehabilitation engineering and robotics.

Speech : Biomechanical challenges in Robotic Exoskeletons

Robotic exoskeletons are predicted to have a market size of 2.8 billion dollars by 2023. It is considered as a valuable human enhancing technology in physical activities as well as an assistive one for disabled people. The technology is at the crossroads of robotics, control, and biomechanical engineering. However the last one is less discussed in the literature. This talk will present the biomechanical challenges and problems encountered in this technology and the recent developments in the area. It briefly reviews the history of development of this technology and the intended applications from military to rehabilitation and the recent developments in the market. Then, the challenges of attaching a robotic kinematic chain to the human body with a complex kinematic will be discussed and the critical research problems will be presented. Finally, the motion planning of such robots and the biomechanical considerations of stability, safety and energy efficiency will be presented.

Biography:

Dr. Davaie Markazi received his BSc and MSc in Mechanical Engineering from Iran University of Technology and Sharif University of Technology in 1982 and 1987, respectively. He received his PhD in Mechanical engineering from McGill University, Canada, in 1995. He is currently a Professor in the School of Mechanical Engineering, Iran University of Science and Technology. Dr. Markazi is one of the founders and the former Chair of the Iranian Society for Mechatronics. His research interests include digital and hybrid control of dynamic systems, adaptive fuzzy sliding control of nonlinear systems, networked control systems, Robotics, and Dynamic Analysis of Brain. Dr. Markazi has published numerous journal and conference papers and two books.

Speech: Recent Advances in Adaptive Fuzzy Sliding Mode Control and its Applications

Many well-known control approaches have already been developed for control of nonlinear uncertain systems in the literature. More specifically, a broad range of methods, namely, the Adaptive Fuzzy Sliding Mode Control (AFSMC) approach have been proposed, with the core idea of achieving robustness and lesser extent of information about the plant, since 1994. A new class of AFSMC methods have been developed and extended in the Mechatronics Lab of IUST since 2008. The proposed methods have been successfully applied to control of SISO/MIMO chaotic systems, MEMS resonators, Mechanisms with friction, Active vortex-induced vibration control, Pneumatic vibration isolation, Wheel slide protection of locomotives, Input-delayed uncertain systems, Anti-lock break system, Under-actuated AUVs, Proportional navigation of uncertain targets, active vibration control of thick piezo-laminated beams and position/force control of Hexapod robots. In this talk, a particular case study, namely, the hybrid position/force control of a Hexapod (Stewart Manipulator) using the AFSMC method will be discussed in a bit more detail. The important advantage of the proposed method is the ability to work with a highly simplified dynamic model of the robot, where the ignored part of the model dynamics has been considered as an state-dependent uncertainty. Such a complex problem has been successfully controlled by an extended version of the AFSMC method. Experimental verifications are performed on the position control loop of the Stewart Manipulator to depict the effectiveness.

Biography:

Mehdi Tale Masouleh received the B. Eng. M. Sc. and Ph.D. degrees in Mechanical engineering (Robotic) from the Laval University, Qubec, Canada, in 2006 , 2007 and 2010, respectively. He is currently a faculty member of Electrical and Computer Engineering at University of Tehran. He is also the director of Human-Robot Interaction Laboratory, known as TaarLab for its Persian abbreviation. His research interests are kinematics, dynamic and design of serial and parallel robotic systems, Humanoid, mobile robots and optimization techniques (interval analysis and convex optimization ) and learning-based approach for robotic applications. He is supervising several undergraduate and graduate students and published several papers in different filed of robotic mechanical systems. Some of industrial projects under the supervision of Mehdi Tale Masouleh are the development of several parallel mechanisms (Tripteron, Delta (3 and 4-DOF), Gough-Stewart platform and a cable-driven parallel robot), Haptic device for dental education simulation and extending a social robot (Sanbot) for Bank Services.

Speech: Human and Robot Interaction, From Academy to Industry

The Human Robot Interaction (HRI) field is rapidly developed by various activities, varying from robots design to creative programming skills and safety considerations. Knowing the fact that robotic science has evolved from desktop computers, to robust mobile and to eventually fill the gap between the virtual and physical worlds, but there are still plenty of tasks required before constructing an environment where robots and humans can interact concordantly with each other. HRI envisions an imminent future where robots scatter everywhere and work with human beings side by side. To exploit successfully robots in public environments, varietal foundations seem essential, such as robot mechanisms, sensation, perception, motion planning and programming. In this lecture, we touch upon several projects conducted in the Human and Robot Interaction Laboratory, where most of them are arisen from industry demands. In order to extend applications of robotic systems to every aspect of human life, which is a high leap for industrializing the HRI field, several mechanical and learning-based methods should be investigated. TaarLab, using both the hands-on experience and theoretical knowledge, is now pioneer for carrying out the foregoing methods by implementing them on its robots. Learning-based methods are crucial due to the fact that they can operate as a logical organ for robotic systems. Motion planning and environmental recognition are some of important duties of robots which require highly-developed learning-based algorithms to successfully interact with humans in public.

Workshop 1: Dynamics of Serial-chain, Tree-type, and Closed-loop Robotic Systems
Tuesday October 6 / 8:00 – 12:00

Saha Workshop- ICRoM 2016

Workshop 1: Dynamics of Serial-chain, Tree-type, and Closed-loop Robotic Systems
Tuesday October 6 / 8:00 – 12:00

Saha Workshop- ICRoM 2016