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: CPS: Medium: An Online Learning Framework for Socially Emerging Mixed Mobility
Emerging mobility systems, e.g., connected and automated vehicles and shared mobility, provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better decisions for improving safety and transportation efficiency. However, different levels of vehicle automation in the transportation network can significantly alter transportation efficiency metrics (travel times, energy, environmental […]
CISE awarded $8.8M to develop the next-generation robotics and autonomous systems workforce
The Boston University Center for Information and Systems Engineering (CISE) received an $8.8 million award to fund a new center called the BU Robotics and Autonomous Systems Teaching and Innovation Center (BU-RASTIC). The award, including $4.4M from the Innovation Institute at the Massachusetts Technology Collaborative (MassTech) and $4.4M matching funds from Boston University, will serve to […]
Advancing Smart Cities with the Internet of Cars
Quicker, Safer and Greener Intersections Intersections with Dynamic Traffic Control In road transport engineering, an intersection is defined as at-grade junction where two or more roads or streets meet or cross. Statistically, it has been evidenced that intersections present a major hurdle in traffic control as they account for the lion’s share of accidents and of […]
NEXTCAR Self-driving Car in Action Advances the Future Internet of Cars
Traffic congestion around the world is worsening, according to transport data firm INRIX. In the U.S. alone, Americans wasted an average of 97 hours in traffic in 2018 – that’s two precious weekends worth of time. Captivity in traffic also costs them nearly $87 billion in 2018, an average of $1,348 per driver. Clearly, the […]
Neuro-Autonomy: Neuroscience-inspired Perception, Navigation, and Spatial Awareness for Autonomous Robots
State-of-the-art Autonomous Vehicles (AVs) are trained for specific, well-structured environments and, in general, would fail to operate in unstructured or novel settings. This project aims at developing next-generation AVs, capable of learning and on-the-fly adaptation to environmental novelty. These systems need to be orders of magnitude more energy efficient than current systems and able to pursue complex goals in […]
Decentralized Optimal Control of Cooperating Networked Multi-agent Systems
Multi-agent systems encompass a broad spectrum of applications, ranging from connected autonomous vehicles and the emerging internet of cars, where the spatial domain may be hundreds of miles with time horizons over hours of days, to micro-air vehicles which operate over meter length and minute time scales, and down to nano-manipulation with nanometer spatial microsecond […]
Highway US-33 – Honda and Cassandras Team Up
Self-driving smart cars used to be something that was seen in the movies; an idea that was too far away to even consider a possible reality. Yet, today we are closer to realizing this dream than ever. Most smart cars on the market come equipped with detectors to alert the driver another vehicle is in […]
Achieving Consensus Among Autonomous Dynamic Agents using Control Laws that Maintain Performance as Network Size Increases
Recent advances in automation and robotics have created a pressing need for new “protocols,” that is, for algorithms or control laws that allow teams of multiple autonomous agents to cooperate and accomplish complex tasks. Unfortunately, many of the best protocols for multi-agent coordination problems suffer from scalability issues, that is, while they perform well when […]
Compressive Robotic Systems: Gaining Efficiency Through Sparsity in Dynamic Environments
This project investigates autonomous control and coordination of a group of robots that are tasked to explore, map, or monitor the environment they are in. The project aims to enhance the capabilities of such a group of robots by integrating Compressive Sensing for data compression. Compressive sensing enables robots to quickly extract information from their […]
CPS: Synergy: Collaborative Research: A Cyber-Physical Infrastructure for the “Smart City”
The project aims at making cities “smarter” by engineering processes such as traffic control, efficient parking services, and new urban activities such as recharging electric vehicles. To that end, the research will study the components needed to establish a Cyber-Physical Infrastructure for urban environments and address fundamental problems that involve data collection, resource allocation, real-time […]