Dr. Metin Sitti received the BSc and MSc degrees in electrical and electronics engineering from Bogazici University, Istanbul, Turkey, in 1992 and 1994, respectively, and the PhD degree in electrical engineering from the University of Tokyo, Tokyo, Japan, in 1999. He was a research scientist at UC Berkeley during 1999-2002. He has been a professor in the Department of Mechanical Engineering and Robotics Institute at Carnegie Mellon University, Pittsburgh, USA since 2002. He is currently a director at the Max Planck Institute for Intelligent Systems in Stuttgart. His research interests include small-scale physical intelligence, mobile microrobotics, bio-inspired materials and miniature robots, soft robotics, and micro-/nanomanipulation. He is an IEEE Fellow. He received the SPIE Nanoengineering Pioneer Award in 2011 and NSF CAREER Award in 2005. He received many best paper, video and poster awards in major robotics and adhesion conferences. He is the editor-in-chief of the Journal of Micro-Bio Robotics.
Mobile Microrobotics, pages: 304, The MIT Press, Cambridge, MA, 2017 (book)
Progress in micro- and nano-scale science and technology has created a demand for new microsystems for high-impact applications in healthcare, biotechnology, manufacturing, and mobile sensor networks. The new robotics field of microrobotics has emerged to extend our interactions and explorations to sub-millimeter scales. This is the first textbook on micron-scale mobile robotics, introducing the fundamentals of design, analysis, fabrication, and control, and drawing on case studies of existing approaches.
The book covers the scaling laws that can be used to determine the dominant forces and effects at the micron scale; models forces acting on microrobots, including surface forces, friction, and viscous drag; and describes such possible microfabrication techniques as photo-lithography, bulk micromachining, and deep reactive ion etching. It presents on-board and remote sensing methods, noting that remote sensors are currently more feasible; studies possible on-board microactuators; discusses self-propulsion methods that use self-generated local gradients and fields or biological cells in liquid environments; and describes remote microrobot actuation methods for use in limited spaces such as inside the human body. It covers possible on-board powering methods, indispensable in future medical and other applications; locomotion methods for robots on surfaces, in liquids, in air, and on fluid-air interfaces; and the challenges of microrobot localization and control, in particular multi-robot control methods for magnetic microrobots. Finally, the book addresses current and future applications, including noninvasive medical diagnosis and treatment, environmental remediation, and scientific tools.
Advanced Materials, May 2017, Back Cover (article)
A facile approach is proposed for superior conformation and adhesion of wearable sensors to dry and wet skin. Bioinspired skin-adhesive films are composed of elastomeric microfibers decorated with conformal and mushroom-shaped vinylsiloxane tips. Strong skin adhesion is achieved by crosslinking the viscous vinylsiloxane tips directly on the skin surface. Furthermore, composite microfibrillar adhesive films possess a high adhesion strength of 18 kPa due to the excellent shape adaptation of the vinylsiloxane tips to the multiscale roughness of the skin. As a utility of the skin-adhesive films in wearable-device applications, they are integrated with wearable strain sensors for respiratory and heart-rate monitoring. The signal-to-noise ratio of the strain sensor is significantly improved to 59.7 because of the considerable signal amplification of microfibrillar skin-adhesive films.
Since its development, ingestible wireless endoscopy is considered to be a painless diagnostic method to detect a number of diseases inside GI tract. Medical related engineering companies have made significant improvements in this technology in last decade; however, some major limitations still residue. Localization of the next generation steerable endoscopic capsule robot in six degreeof-freedom (DoF) and active motion control are some of these limitations. The significance of localization capability concerns with the doctors correct diagnosis of the disease area. This paper presents a very robust 6-DoF localization method based on supervised training of an architecture consisting of recurrent networks (RNN) embedded into a convolutional neural network (CNN) to make use of both just-in-moment information obtained by CNN and correlative information across frames obtained by RNN. To our knowledge, our idea of embedding RNNs into a CNN architecture is for the first time proposed in literature. The experimental results show that the proposed RNN-in-CNN architecture performs very well for endoscopic capsule robot localization in cases vignetting, reflection distortions, noise, sudden camera movements and lack of distinguishable features.
Background: Successful gene delivery requires overcoming both systemic and intracellular obstacles before the nucleic acid cargo can successfully reach its tissue and subcellular target location.
Materials & Methods: Non-viral mechanisms to enable targeting while avoiding off-target delivery have arisen via biological, chemical, and physical engineering strategies.
Discussion: Herein we will discuss the physical parameters in particle design that promote tissue- and cell-targeted delivery of genetic cargo. We will discuss systemic concerns, such as circulation, tissue localization, and clearance, as well as cell-scale obstacles, such as cellular uptake and nucleic acid packaging.
Conclusion: In particular, we will focus on engineering particle shape and size in order to enhance delivery and promote precise targeting. We will also address methods to program or change particle shape in situ using environmentally triggered cues.
IEEE Robotics and Automation Letters, 2(2):927-934, IEEE, January 2017 (article)
The risk of side effects from thrombolytic agents can be minimized by using smaller doses, assisted by mechanical rubbing against blood clots using helical robots. Quantifying this observation, we study the influence of rubbing against clots on their removal rate in vitro. First, we present a hydrodynamic model of the helical robot based on the resistive-force theory to investigate the rubbing behavior of the clots using robot driven by two rotating dipole fields. Second, we experimentally evaluate the influence of the rubbing on the removal rate of the blood clots. Not only do we find that the removal rate of mechanical rubbing (-0.56 ± 0.27 mm3 /min) is approximately three times greater than the dissolution rate of chemical lysis using streptokinase (-0.17 ± 0.032 mm3/min), but we also show that this removal rate can be controlled via the rubbing speed of the robot.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems