Special Topics Courses
Professor Taskin Padir
Wednesdays 6:00pm - 8:50pm - SL406
This course addresses the what (modeling), how (design) and why (analysis) of systems through the use of model-based design process. System models will be essential to four key aspects of the design process, derivation of executable specifications, hardware and software design based on simulations, implementation by code generation, and continuous testing and verification. Model-based design can be an effective tool to ensure safe, efficient and reliable operation of cyber-physical systems in which computation and communication are tightly integrated with physical processes. Topics may include modeling continuous and discrete dynamics, heterogeneous models, hybrid systems, stochastic models, models of computation, analysis and design of embedded control systems with applications in robotics, system simulation, validation and verification techniques, time-critical systems and human-in-the-loop cyber-physical systems.
The examples throughout the course will be drawn from practical robot applications as robotics requires a whole system design approach at the cross-section of environmental models, physical components and algorithms. Course projects will emphasize model-based design for control of robotic systems.
Prerequisites: linear algebra and differential equations; embedded systems; linear systems and control theory or consent of the instructor.
Introduction to Biomechanics and Robotics
Professor Marko Popovic
Tuesdays and Thursdays 4:00pm - 5:20pm - OH218
This is an introductory course to Biomechanics and Robotics. We will discuss and illustrate with number of examples how biomechanical scientific studies can inform advanced robotics engineering. We will also show that advance biologically inspired engineering can help us better understand the living systems. Modern Biomechanics and Robotics can be thought of as a unified discipline dealing with both biological and artificial “organisms”, i.e. discipline that goes well beyond the individual subjects of Biomechanics, Robotics, Biomedical Engineering, Biomechatronics, Biologically Inspired Robotics, etc.; unified discipline that holds a promise to be one of the most influential innovative research directions defining the 21st century. The following topics will be addressed: Biological and Artificial sensors, actuators and control, Orthotics Biomechanics and Robotics, Prosthetic Biomechanics and Robotics: Artificial Organs and Limbs, Rehabilitation Robotics and Biomechanics: Therapy, Assistance and Clinical Evaluation, Human-Robot Interaction and Robot Aided Living for Healthier Tomorrow, Sports, Exercise and Games: Biomechanics and Robotics, Robot-aided Surgery, Biologically Inspired Robotics and Micro-(bio)robotics, New Technologies and Methodologies in Medical Robotics and Biomechanics, Neural Control of Movement and Robotics Applications, Applied Musculoskeletal Models and Human Movement Analysis. This course is intended for graduate students but advanced undergraduate students are also welcome. There will be 6 to 7 problem sets as well as an oral and written final project presentation by each student. Prof Popovic co-founded the MIT Biomechatronics Group (ex MIT Leg Lab). He chaired the IEEE EMBC Biomechanics and Robotics Theme in 2011. The lectures for this course are curently in press; this will be one of the first if not the first textbook on this popular theme.
Professor Cagdas Onal
Soft robotics studies ‘intelligent’ machines and devices that incorporate some form of compliance in their mechanics. Elasticity is not a byproduct but an integral part of these systems, responsible for inherent safety, adaptation and part of the computation in this class of robots. This course will cover a number of major topics of soft robotics including but not limited to design and fabrication of soft systems, elastic actuation, embedded intelligence, soft robotic modeling and control, and fluidic power. Students will implement new design and fabrication methodologies of soft robots, read recent literature in the field, and complete a project to supplement the course material. Existing soft robotic platforms will be available for experimental work.
Prerequisites: Differential equations, linear algebra, stress analysis, kinematics, embedded programming.
Professor Eduardo Torres-Jara
Monday - Wednesday 9:00am - 10:20am - AK232
This course introduces an approach to robotics called Sensitive Robotics. This approach allows robots to perform complex tasks by using large array of sensors that provide information relevant to the task at hand. The course studies the hardware and software implications of this approach. At the hardware level, we discuss the mechanical and electrical characteristic of the sensors and actuators, the design consideration of arms and limbs, and the hardware architecture alternatives. At the software level, we discuss the implications that the hardware changes have in the software architecture, and the control algorithms. Machine learning techniques, needed to deal with large array of sensors, are also covered. The case of robotic manipulation (sensitive manipulation) is introduced as an example of this approach and it is expanded to walking, flying and swimming robots.
Prerequisites: Consent of the instructor.
Professor Dmitry Berenson
Tuesday - Thursday 1:00pm - 2:20pm - SH106
Motion planning is the study of algorithms that reason about the movement of physical or virtual entities. These algorithms can be used to generate sequences of motions for many kinds of robots, robot teams, animated characters, and even molecules. This course will cover the major topics of motion planning including (but not limited to) planning for manipulation with robot arms and hands, mobile robot path planning with non-holonomic constraints, multi-robot path planning, high-dimensional sampling-based planning, and planning on constraint manifolds. Students will implement motion planning algorithms in open-source frameworks, read recent literature in the field, and complete a project that draws on the course material. The PR2 robot will be available as a platform for class projects.
Prerequisites: Undergraduate Linear Algebra, experience with 3D geometry, and significant programming experience.
Professor Sonia Chernova
Tuesday - Thursday 3:30pm - 4:50pm - AK108
This course focuses on human-robot interaction and social robot learning, exploring the leading research, design principles and technical challenges we face in developing robots capable of operating in real-world human environments. The course will cover a range of multidisciplinary topics, including physical embodiment, mixed-initiative interaction, multi-modal interfaces, human-robot teamwork, learning algorithms, aspects of social cognition, and long-term interaction. These topics will be pursued through independent reading, class discussion, and a final project.
Prerequisites: Mature programming skills and at least undergraduate level knowledge of AI. No hardware experience is required.
Professor Gregory S. Fischer
Monday - Wednesday 3:00pm - 4:50pm - GH227
This course will provide an overview of a multitude of biomedical applications of robotics. Applications covered include: image-guided surgery, percutaneous therapy, localization, robot-assisted surgery, simulation and augmented reality, laboratory and operating room automation, robotic rehabilitation, and socially assistive robots. Specific subject matter includes: medical imaging, coordinate systems and representations in 3D space, robot kinematics and control, validation, haptics, teleoperation, registration, calibration, image processing, tracking, and human-robot interaction. Topics will be discussed in lecture format followed by interactive discussion of related literature. The course will culminate in a team project covering one or more of the primary course focus areas.
Recommended background: Linear algebra, RBE 501 or equivalent