Automation & Control
Automation & Control combines engineering with machine-learning in order to provide industrial systems with the information necessary to work in an automatic and controlled manner. Research areas include: atomic force microscopy, bio-inspired control, discrete-event systems, formal languages for robot mission specification, hybrid systems, image-guided surgery, networked control systems, robot path planning and control, robotic swarms, and UAV flight control.
Collaborative Research: Closed-loop Optimization and Control of Physical Networks Subject to Dynamic Costs, Constraints, and Disturbances
This project will advance a fundamentally new control framework, utilizing streams of heterogeneous data to optimize the behavior of complex and dynamic networked systems with pervasive sensing and computing capabilities, operating in uncertain and changing environments. Existing workhorse control and optimization methodologies assume a large separation of time scales, sufficient to justify complete decoupling of […]
Collaborative Research: SaTC: CORE: Small: Research on Concurrent Inauthentic Account and Narrative Detection
Inauthentic accounts are commonly used by adversaries on online platforms to carry out fraudulent activities like false advertising, scams, and personal threats. These accounts appear to belong to real people, but actually portray fictitious personas and are controlled by miscreants through semi-automated means to deliver potentially harmful content. Promptly detecting inauthentic accounts and fraudulent content […]
The Future of Driving: Control Barrier Functions and the Internet of Vehicles
The National Highway Traffic and Safety Association reports that 94% of serious car crashes are due to human error. Christos Cassandras, Boston University Distinguished Professor of Electrical & Computer Engineering, Head of the Division of Systems Engineering, and a co-founder of the Center for Information & Systems Engineering (CISE), has made monumental contributions to the […]
Reinforcement Learning: A More Efficient Way for Robots to Learn
Robot nurses — myth or reality? Although this may sound far-fetched, there are already hospitals in which robots assist nurses by bringing them tools, allowing the nurses to focus on providing care to their patients more efficiently. Vittorio Giammarino, a fifth-year PhD candidate (SE) at Boston University, hopes that his work can be useful for […]
Shifting the Purpose of Robots From Serving Humans to Collaboration
In dire situations like fires, time is of the essence. Firefighters need to work quickly to extinguish the fire and rescue any people. However, with emerging technologies like robots, putting out fires might become easier. Mela Coffey 3rd year ME PhD Candidate (Advisor: Alyssa Pierson) is interested in contributing to collaborative human-robot systems and human-robot […]
Learning From Animal Behaviors to Inform Control Systems
You may be familiar with the term “blind as a bat”, which is used to describe someone who has poor eyesight. However, recent research on animal behavior by CISE affiliate and Distinguished Professor of Engineering John Baillieul (ME, ECE, SE) found that this phrase is a misconception and many species of bats rely on visual […]
Sabelhaus Research: Advancing the Safety of Soft Robots for Human Interactions
The emergence of soft robots will enable safe human interactions which will allow robots to assist in the industrial, medical, automotive and space industries. College of Engineering Professor Andrew Sabelhaus (ME, SE), has been working on making soft robots safer to improve these human interaction tasks, in areas such as medicine, as well as […]
Unified Vision-Based Motion Estimation and Control for Multiple and Complex Robots
The project enables teams of robots to collaborate on physical tasks, such as assembling a building from prefabricated components under the direction of a human worker. In such settings, each robot might be equipped with cameras to orient itself and have some limitations on how it can move. To achieve the robotic team’s goals, each […]
FRR: Towards Robust and Perceptual Inclusive Mobile Robots
As prototypical intelligent mobile systems, from autonomous vehicles to delivery robots, move from their controlled development labs into the real-world, their impact on individuals with disabilities becomes discernible. An intelligent system that fails to account for diverse reactions and mobility characteristics among individuals can have dire consequences. For example, a delivery robot may inadvertently cause […]
New Technology Could Predict When Someone’s Mobility is Declining
CISE Faculty Affiliate Roberto Tron uses Visual-Inertial Filtering for Clinically-Relevant Human Walking Quantification As we age, the likelihood of falling and getting injured increases. But what if we could prevent these accidents from happening? CISE faculty affiliate Roberto Tron is working on preventing injuries by monitoring mobility through cameras, sensors, machine learning, and estimation algorithms […]