ARAS PACR Group Introduction File
Increasing performance demands necessitate design of new types of robots with larger work space, being capable to perform at higher accelerations. In a cable-driven redundant parallel manipulator (CDRPM), the linear actuators of parallel manipulators are replaced with electrical powered cable drivers, which lead immediately to a larger work space. The idea of using cable driven redundant parallel manipulators, are not limited to only the applications where a very large work space is required, and this idea is effectively penetrated in the applications where precise and stiff robot is required to operate in high accelerations within a relatively larger work space than that attainable in conventional parallel robots. In our lab , several applications in which a CDRPM is used are introduced, and the challenging issues in the optimal kinematics structure, dynamics formulation, and control of such structure are studied.
ARAS AR Group Introduction File
This research theme start its root from IROS 2005 Conference, where the overwhelming research work presented on SLAM in addition to the upcoming industrial needs motivates rigorous work on this area. The first Master student worked on SLAM in the group was Ali Agha Mohammadi, who elaborates on different aspect of visual SLAM as well as implementation of Laser range finder based localization and mapping. Very soon other researchers explored a wide spectrum of research work on the consistency of EKF -based SLAM algorithms, as well as other state-of-the-art of techniques developed in this area such as FastSLAM. Some works are done on developing more suitable and faster optimization techniques being developed for iSAM algorithms.The research results was shortly used in different robotic platforms developed in the group. Among many works done in this area, one may mention the projects implemented on our Silver robot for exploration in an unknown indoor environment, further promoted for obstacle avoidance of static and dynamic objects. The implementation of SLAM algorithms in outdoor applications using stereo vision camera implemented on our other robotic platform Melon, was among the other challenges being fully worked out in the group. Soon we realized the importance and challenges existing in the 3D Mapping and localization, and a long term project was funded to develop a suitable 3D representation of the environment based on RGB-D sensory data. Using Kolmogorov complexity measures as well as Nurbs smoothing functions enables us to develop a very effective and computationally effective representation method for 3D visual data. Furthermore, trajectory planning and nonlinear control for navigation has been considered in the implementation of these techniques on autonomous ground robots as well as autonomous areal drones.
ARAS SR Group Introduction File
The surgical robotics group aims at developing new robotics-based technologies for robot-assisted surgery and surgery training applications. This includes the design and integration of mechanical and electrical components as well as the development of innovative control structures for these systems. These robotic systems will enhance the safety and efficiency of medical surgeries which leads to more satisfaction in all of the people dealing with the healthcare systems especially the patients, the surgeons, and the residents. This group has enjoyed the collaboration and consultation of several national and international partners in the fields of engineering and medical science.
ARAS MR Group Introduction File
Virtual Reality in Medicine is a three-dimensional teaching tool used across the field of healthcare as a means of both education and instruction. Virtual Reality commonly refers to healthcare simulation environments in which learners can experience visual stimuli delivered via computer graphics and other sensory experiences. This advanced technology allows learners to obtain the knowledge and understanding necessary to perform a number of tasks and procedures involving the human body, without ever having to practice on a live patient. Central to this technology is the immersive capacity of Virtual Reality, e.g. the simulated environment surrounds a learner’s perceptual field. This means that the user feels psychologically present in the digital world, rather than in their physical reality. Utilized to educate learners on diagnosis, treatment, rehabilitation, surgery, counseling techniques and more, Virtual Reality in medicine is helping to train the next generation of healthcare professionals. This medical simulation technology has shown to have a number of benefits, such as allowing learners to practice their skills without fear of error causing potentially life-threatening impacts. The Virtual Reality tools still provide the hands-on experience required to acquire a familiarity and comfort in performing procedures, but in a safe and controlled setting. Therefore, as learners make mistakes, they can be thoroughly corrected in real-time and without risk. As Virtual Reality modules still require interaction, skills are able to become second nature before they are applied in real world scenarios. ARAS Mixed Reality research group, is aimed to build a simulator of vitrectomy and cataract surgery using virtual reality to provide a completely similar environment for real surgery for eye surgery residents. The Objective of research in this group will be completed with a joint collaboration research with Surgical Robotic (SR) research group of ARAS. We aim to incorporate the mixed reality simulation tool developed in this group to ARASH:ASiST, the product developed in SR group for Vitrectomy training.
ARAS Dynamical Systems Analysis & Control Group Introduction File
Two principal aims confront us. Firstly, to study dynamical systems theory, including methods for analyzing differential equations and iterated mappings, which draws on analysis, geometry, and topology. We specially concentrate on one of the most important theories in dynamical systems theory and control theory which comprises various topics such as stability, controllability and observability, robustness, identification, optimality. Secondly, to apply and to tailor aforementioned theories to practical systems. Some of the practical systems which we have recently been dealing with are brain-machine interface systems.