Assuring the Safety, Security and Reliability of Medical Device Cyber Physical Systems (NSF CPS)

The objective of this research is to establish a new development paradigm that enables the effective design, implementation, and certification of medical device cyber-physical systems. The approach is to pursue the following research directions: 1) to support medical device interconnectivity and interoperability with network-enabled control; 2) to apply coordination between medical devices to support emerging clinical scenarios; 3) to close the loop and enable feedback about the condition of the patient to the devices delivering therapy; and 4) to assure safety and effectiveness of interoperating medical devices. Novel design methods and certification techniques will significantly improve patient safety. The introduction of closed-loop scenarios into clinical practice will reduce the burden that caregivers are currently facing and will have the potential of reducing the overall costs of health care.

Greater Philadelphia Innovation Cluster (GPIC) for Energy Efficient Buildings (DoE HUB)

The Greater Philadelphia Innovation Cluster (GPIC) for Energy Efficient Buildings received $129 million from the Federal Government's Energy Regional Innovation Cluster (E-RIC) Initiative. The award included $122 million from the U.S. DOE to create the GPIC/HUB to develop innovative energy efficient building technologies, designs and systems. The GPIC/HUB goal is to transform the commercial building retrofit and new construction processes into a systems-delivery industry, and demonstrate building operational energy savings of 50% by 2013-2015 in a scalable, repeatable and cost effective manner across a broad building stock, while preserving workplace quality.

Heterogeneous Unmanned Networked Teams (ONR HUNT)

The grand challenge for this multi-university project is to push the state-of-the-art in complex, time-critical mission planning and execution for large numbers of heterogeneous vehicles collaborating with humans. Sophisticated cooperation among intelligent biological organisms, including humans, will offer critical insight and solution templates for many hard engineering problems. To meet this challenge, we have a assembled an interdisciplinary team of leading researchers who have pioneered work in artificial intelligence, vehicle control and robotics, cognitive psychology and human factors, biology, and political economics. This multi-university project is led by the University of Pennsylvania and will be performed in collaboration with the Georgia Institute of Technology, the University of California at Berkeley, medicalnd Arizona State University.

Quantitative Analysis and Design of Control Networks (NSF CPS)

Control networks are wireless substrates for industrial automation control, such as the WirelessHART and Honeywell's OneWireless, and have fundamental differences over their sensor network counterparts as they also include actuation and the physical dynamics. The approach of the project is based on using time-triggered communication and computation as a unifying abstraction for understanding control networks. Time-triggered architectures enable the natural integration of communication, computation, and physical aspects of control networks as switched control systems. The time-triggered abstraction will serve for addressing the following interrelated themes: Optimal Schedules via Quantitative Automata, Quantitative Analysis and Design of Control Networks: Wireless Protocols for Optimal Control: Quantitative Trust Management for Control Networks. Our results will be integrated into control networks that are compatible with both WirelessHART and OneWireless specifications.

Scalable swarms of autonomous robots and mobile sensors (ARO MURI)

This multi-university project brings together experts in artificial intelligence, control theory, robotics, systems engineering and biology with the goal of understanding swarming behaviors in nature and applications of biologically-inspired models of swarm behaviors to large networked groups of autonomous vehicles. Our main goal is to develop a framework and methodology for the analysis of swarming behavior in biology and the synthesis of bio-inspired swarming behavior for engineered systems. This multi-university project is led by the University of Pennsylvania and will be performed in collaboration with the Massachusets Institute of Technology, the University of California at Berkeley, the University of California at Santa Barbara, and Yale University.

Micro Autonomous Systems & Technology (ARL CTA MAST)

The Micro Autonomous Systems Technologies (MAST) consists of four research centers focusing on microsystem mechanics, microelectronics, autonomous operations, and systems integration. The objective of the consortium is to develop autonomous, collaborative ensembles of agile, mobile microsystems to enhance tactical situational awareness in urban and complex terrain for small unit operations. The University of Pennsylvania is leading in the autonomous operation research center. Our emphasis is on processing for autonomous operations, which will provide the fundamental underpinnings for autonomous operation of distributed, mobile, multi-modal sensing micro-systems.

Robust testing by testing robustness of embedded systems (NSF EHS)

In recent years, the idea of the model-based design paradigm is to develop design models and subject them to early analysis, testing, and validation prior to their implementation. Simulation-based testing ensures that a finite number of user-defined system trajectories meet the desired specification. Even though computationally inexpensive simulation is ubiquitous in system design, it suffers from incompleteness, as it is impossible or impractical to test all system trajectories. On the other hand, verification methods enjoy completeness by showing that all system trajectories satisfy the desired property. This project brings together leading experts in embedded control, hybrid systems, and software monitoring and testing to develop the foundations of a modern framework for testing the robustness of embedded hybrid systems. The central idea that this project is centered around is the notion of a robust test, where the robustness of nominal test can be computed and used to infer that a tube of trajectories around the nominal test will yield the same qualitative behavior.

Situation undersanding bot through language and environment (ARO MURI)

This multi-university project brings together experts in linguistics, computational linguistics, artificial intelligence, machine learning, and robotics with the goal of developing a language for communication between humans and robots, where robots are responding to a changing environment and reporting on the relevant aspects of those changes. We will develop a broad range of concepts, which will ultimately enable designers to develop powerful communication methods between robots and humans, enabling humans to communicate goals and intentions as well as direct commands to robots in a natural, effective way. This multi-university project is led by the University of Pennsylvania and will be performed in collaboration with the University of Massachusstts at Amherst and the University of Massachusets at Lowell.