The objective of this research is to develop new principles for creating and comparing models of skilled human activities, and to apply those models to systems for teaching, training and assistance of humans performing these activities. The models investigated will include both hybrid systems and language-based models. The research will focus on modeling surgical manipulations during robotic minimally invasive surgery. Models for expert performance of surgical tasks will be derived from recorded motion and video data. Student data will be compared with these expert models, and both physical guidance and information display methods will be developed to provide feedback to the student based on the expert model. The intellectual merit of this work lies in the development of a new set of mathematical tools for modeling human skilled activity. These tools will provide new insights into the relationship between skill, style, and content in human motion. Additional intellectual merit lies in the connection of hybrid systems modeling to language models, the creation of techniques for automated training, and in the assessment of new training methods. The broader impact of this research will be the creation of automated methods for modeling and teaching skilled human motion. These methods will have enormous implications for the training and re-training of the US workforce. This project will also impact many diversity and outreach activities, including REU programs and summer camps for K-12 outreach. The senior personnel of this project also participate in the Robotic Systems Challenge and the Women in Science and Engineering program.

The objective of this research is to develop an integrated methodology for control system design in situations where disturbances primarily result from routine human behavior, as, for example, in future artificial pancreas systems where meals and exercise are the main disturbances affecting blood glucose concentration. The approach is to recognize that human behavioral disturbances (i) are generally random but cannot be treated as zero-mean white noise processes and (ii) occur with statistical regularity but cannot be treated as periodic due to natural variation in human behavior. This emerging class of problems requires (i) the derivation of new mathematical representations of disturbances for specific applications and (ii) the formulation of new stochastic control models and algorithms that exploit statistical regularity in the disturbance process. The intellectual merit of the proposed research stems from the fact that it explicitly recognizes a new class of disturbances, human behavioral disturbances, seeking to develop an integrated approach to statistically characterizing and responding to future perturbations, adapting gracefully to uncertainty about the future. The anticipated research outcomes will be relevant in diverse fields, including stochastic hybrid control and human automation interaction. As a broader implication, the proposed research will enable the design of future field deployable artificial pancreas systems, potentially improving the lives of 1.5 million Americans suffering from Type 1 diabetes. With help from the two graduate students funded by the project, the principle investigator will supervise a Capstone design course, exposing undergraduates to various aspects of control under human behavioral disturbances.

The objective of this research is the transformation from static sensing into mobile, actuated sensing in dynamic environments, with a focus on sensing in tidally forced rivers. The approach is to develop inverse modeling techniques to sense the environment, coordination algorithms to distribute sensors spatially, and software that uses the sensed environmental data to enable these coordination algorithms to adapt to new sensed conditions. This work relies on the concurrent sensing of the environment and actuation of those sensors based on sensed data. Sensing the environment is approached as a two-layer optimization problem. Since mobile sensors in dynamic environments may move even when not actuated, sensor coordination and actuation algorithms must maintain connectivity for the sensors while ensuring those sensors are appropriately located. The algorithms and software developed consider the time scales of the sensed environment, as well as the motion capabilities of the mobile sensors. This closes the loop from sensing of the environment to actuation of the devices that perform that sensing. This work is addresses a challenging problem: the management of clean water resources. Tidally forced rivers are critical elements in the water supply for millions of Californians. By involving students from underrepresented groups, this research provides a valuable opportunity for students to develop an interest in engineering and to learn first hand about the role of science and engineering in addressing environmental issues.

The objective of this research is the transformation from static sensing into mobile, actuated sensing in dynamic environments, with a focus on sensing in tidally forced rivers. The approach is to develop inverse modeling techniques to sense the environment, coordination algorithms to distribute sensors spatially, and software that uses the sensed environmental data to enable these coordination algorithms to adapt to new sensed conditions. This work relies on the concurrent sensing of the environment and actuation of those sensors based on sensed data. Sensing the environment is approached as a two-layer optimization problem. Since mobile sensors in dynamic environments may move even when not actuated, sensor coordination and actuation algorithms must maintain connectivity for the sensors while ensuring those sensors are appropriately located. The algorithms and software developed consider the time scales of the sensed environment, as well as the motion capabilities of the mobile sensors. This closes the loop from sensing of the environment to actuation of the devices that perform that sensing. This work is addresses a challenging problem: the management of clean water resources. Tidally forced rivers are critical elements in the water supply for millions of Californians. By involving students from underrepresented groups, this research provides a valuable opportunity for students to develop an interest in engineering and to learn first hand about the role of science and engineering in addressing environmental issues.

The objective of this research is to develop a framework for the development and deployment of next-generation medical systems consisting of integrated and cooperating medical devices. The approach is to design and implement an open-source medical device coordination framework and a model-based component oriented programming methodology for the device coordination, supported by a formal framework for reasoning about device behaviors and clinical workflows. The intellectual merit of the project lies in the formal foundations of the framework that will enable rapid development, verification, and certification of medical systems and their device components, as well as the clinical scenarios they implement. The model-based approach will supply evidence for the regulatory approval process, while run-time monitoring components embedded into the system will enable "black box" recording capabilities for the forensic analysis of system failures. The open-source distribution of tools supporting the framework will enhance its adoption and technology transfer. A rigorous framework for integrating and coordinating multiple medical devices will enhance the implementation of complicated clinical scenarios and reduce medical errors in the cases that involve such scenarios. Furthermore, it will speed up and simplify the process of regulatory approval for coordination-enabled medical devices, while the formal reasoning framework will improve the confidence in the design process and in the approval decisions. Overall, the framework will help reduce costs and improve the quality of the health care.

The objective of this research is to investigate and develop methods and tools for the analysis and verification of cyber-physical systems. The approach is to augment the methods and tools that have been developed at the University of Utah and the University of South Florida for modeling and verification of asynchronous and analog/mixed-signal circuits to address challenges in cyber-physical system verification. This research will develop a unified framework with methods and tools which include an integrated formalism to comprehensively model discrete/continuous, functional/timing, synchronous/asynchronous, and deterministic/stochastic behavior. These tools will also include algorithms to analyze behavior and verify that it satisfies the correctness requirements on functionality, timing, and robustness. Finally, they will include abstraction and compositional reasoning approaches to enable large systems to be analyzed and verified efficiently. Since cyber-physical systems are becoming ubiquitous, improvements in such systems such as higher reliability, better fault-tolerance, improved performance, and lower design costs will have tremendous positive impact on society. Results from this research will be transferred to the cyber-physical systems community and other application domains by both publishing papers in related conferences and journals as well as by freely distributing tools via the Internet. Both graduate and undergraduate students will be engaged in this multi-institutional research where they will be exposed to the latest research in formal and probabilistic analysis. Early involvement of undergraduate students may help encourage them to attend graduate school. This research project will also recruit underrepresented and female students to allow it to reach broader audiences.

The objective of this research is the development of novel control architectures and computationally efficient controller design algorithms for distributed cyber-physical systems with decentralized information infrastructures and limited communication capabilities. Active safety in Intelligent Transportation Systems will be the focus cyber-physical application. For the successful development and deployment of cooperative active safety systems, it is critical to develop theory and techniques to design algorithms with guaranteed safety properties and predictable behavior. The approach is to develop a new methodology for the design of communicating distributed hybrid controllers by integrating in a novel manner discrete-event controller design and hybrid controller design and optimization. The methodology to be developed will exploit problem decomposition and will have significant technological impact for a large class of cyber-physical systems that share features of modularity in system representation, partial information, and limited communication. The focus on distributed control strategies with limited communication among agents is addressing an important gap in existing control theories for cyber-physical systems. The approach will mitigate the computational limitations of existing approaches to control design for hybrid systems. Given the focus on cooperative active safety in Intelligent Transportation Systems, the results of this effort will have significant societal impact in terms of increased traffic safety and reduced number and severity of accidents. The broader impacts of this proposal also include involvement of high-school and undergraduate students and curriculum development by incorporating results of research into existing courses on cyber-physical systems.