The objective of this research is the design of innovative routing, planning and coordination strategies for robot networks, and their application to oceanography. The approach is organized in three synergistic thrusts: (1) the application of queueing theory and combinatorial techniques to networked robots performing sequential tasks, (2) the design of novel distributed optimization and coordination schemes relying only on asynchronous and asymmetric communication, (3) the design of practical routing and coordination algorithms for the USC Networked Aquatic Platforms. In collaboration with oceanographers and marine biologists, the project aims to design motion, communication and interaction protocols that maximize the amount of scientific information collected by the platforms. This proposal addresses multi-dimensional problems of relevance in Engineering and Computer Science by unifying fundamental concepts from multiple cyberphysical domains (robotics, autonomy, combinatorics, and network science). Our team has expertise in a broad range of scientific disciplines, including control theory and theoretical computer science and their applications to multi-agent systems, robotics and sensor networks. The proposed research will have a positive impact on the emerging technology of autonomous and reliable robotic networks, performing a broad range of environmental monitoring and logistic tasks. Our educational and outreach objectives are manifold and focus on (1) integrating the proposed research themes into undergraduate education and research, e.g., via the existing NSF REU site at the USC Computer Science Department, and (2) mounting a vigorous program of outreach activities, e.g., via a well-developed collaboration with the UCSB Center for Science and Engineering Partnerships.

The objective of this research is to check correct functioning of cyber-physical systems during their operation. The approach is to continuously monitor the system and raise an alarm when the system seems to exhibit an erroneous behavior. Correct functioning of cyber-physical systems is of critical importance. This is more so in safety critical systems like medical, automotive and other applications. The approach employs hybrid automata for specifying the property to be monitored and for modeling the system behavior. The system behavior is probabilistic in nature due to noise and other factors. Monitoring such systems is challenging since the monitor can only observe system outputs, but not it's state. Fundamental research, on defining and detecting whether a system is monitorable, is the focus of the work. The project proposes accuracy measures and cost based metrics for optimal monitoring. The project is developing efficient and effective monitoring techniques, based on product automata and Partially Observable Markov Decision Processes. The results of the project are expected to be transformative in ensuring correct operation of systems. The results will have impact in many areas of societal importance and utility for daily life, such as health care, nursing/rehabilitation, automotive systems, home appliances, and more. The benefits in nursing/rehabilitation emanate from the deployment of advanced technologies to assist caregivers. This can lead to improved health and quality of life of older patients at reduced costs. The project includes education and outreach in the form of K-12 outreach and involvement of undergraduate and graduate students in research. The project is committed to involving women and minorities in education and research.

The objective of this research is the design of innovative routing, planning and coordination strategies for robot networks, and their application to oceanography. The approach is organized in three synergistic thrusts: (1) the application of queueing theory and combinatorial techniques to networked robots performing sequential tasks, (2) the design of novel distributed optimization and coordination schemes relying only on asynchronous and asymmetric communication, (3) the design of practical routing and coordination algorithms for the USC Networked Aquatic Platforms. In collaboration with oceanographers and marine biologists, the project aims to design motion, communication and interaction protocols that maximize the amount of scientific information collected by the platforms. This proposal addresses multi-dimensional problems of relevance in Engineering and Computer Science by unifying fundamental concepts from multiple cyberphysical domains (robotics, autonomy, combinatorics, and network science). Our team has expertise in a broad range of scientific disciplines, including control theory and theoretical computer science and their applications to multi-agent systems, robotics and sensor networks. The proposed research will have a positive impact on the emerging technology of autonomous and reliable robotic networks, performing a broad range of environmental monitoring and logistic tasks. Our educational and outreach objectives are manifold and focus on (1) integrating the proposed research themes into undergraduate education and research, e.g., via the existing NSF REU site at the USC Computer Science Department, and (2) mounting a vigorous program of outreach activities, e.g., via a well-developed collaboration with the UCSB Center for Science and Engineering Partnerships.

The objective of this research is the creation of a coastal observing system that enables dense, in situ, 4D sensing through networked, sensor-equipped underwater drifters. The approach is to develop the technologies required to deploy a swarm of autonomous buoyancy controlled drifters, which are vehicles that can control their depth, but are otherwise carried entirely by the ocean currents. Such Lagrangian sampling promises to deliver a wealth of new data, ranging from applications in physical oceanography (mapping 3D currents), biology (observing the dispersion of larvae and nutrients), environmental science (tracking coastal pollutants and effluents from storm drains), and security (monitoring harbors and ports). This observing system fundamentally requires accurate positions of the drifters (to interpret the spatial correlations of data samples), swarm control algorithms (to achieve desired sampling topologies), and wireless communication (to coordinate between the individual drifters). This research will create distributed techniques to self-localize the drifter swarm, novel swarm control algorithms that enable topology manipulation while purely leveraging the stratified flow environment, and efficient wireless underwater communication for information sharing. This project has significant societal impact and educational elements. Underwater drifter swarms will enable novel insights into a wide array of scientific questions, including understanding plankton transport, accumulation and dispersion as well as monitoring harmful algal blooms. Undergraduates will play an active role in many aspects of this project, thereby offering them a uniquely interdisciplinary experience. Finally, outreach to high school students will occur through the UCSD COSMOS summer program.

The objective of this research is to develop methods and tools for designing, implementing and verifying medical robotics. The approach is to capture the computational work-flow of systems with cyber, physical and biological components, to verify that work-flow and to synthesize systems from the work-flow model. The focusing application of this research is MRI-guided, high-frequency ultrasonic tumor ablation. MRI-guided ultrasonic tumor ablation poses challenges beyond the scope of current verification techniques. Medicine is filled with highly non-linear biological systems, which puts them at the frontier of mathematically rigorous correctness checking and verification. For instance, in this research, guaranteeing the safety of a cancer patient undergoing treatment will require verifying against Pennes bioheat equation, a non-linear differential equation with dozens of environmental factors. This research tackles such complexity using tiers of abstractions to efficiently, precisely and safely approximate the behavior of each component of a system. To ensure a faithful implementation of controllers, this research will investigate synthesizing the control code directly from the verified model in a correct by construction manner. The project will help develop the most appropriate family of formal methods for handling the safety and correctness challenges in the area of medical robotics. It directly addresses the CPS agenda of methods and tools by proposing formal techniques that bridge the gap between the cyber and physical elements. It will train manpower in cross-disciplinary areas through new seminars, workshops and courses. And, last but not least, the project will make a direct humanitarian impact on the well-being of society.

Complex surgical procedures in hospitals are increasingly aided by robotic surgery systems, often at the request of patients. These systems allow greatly increased precision, reach and flexibility to the surgeon. However, their powerful capabilities entail substantial system complexity in both hardware and software. The high probability of serious injuries should a malfunction occur calls for rigorous assessment and monitoring of the reliability and safety of these cyber-physical systems. In this research project, a framework for assessing and monitoring the reliability and safety of robotic surgery systems during development, field testing, and general deployment is being developed. The proposed framework complements existing techniques used in earlier phases of validation by taking into account how surgeons actually use a robotic surgery system, how it is affected by operating conditions, and how its observable behavior is related to its hardware and software dynamics. Before deployment, this framework uses accurate simulations to assess pre-clinical reliability. After deployment, the framework uses data collection through online monitoring of the system as it is being used in the field, followed by analysis to obtain assessments of operational reliability and safety. The collected data is also used to improve the simulations for future testing. The framework also aims to support post-market surveillance of these systems by providing a workable basis for reassessing reliability and safety properties after system maintenance. The developed tools and methods will also have applications in the validation of safety and reliability of other medical devices with embedded software and other cyber-physical systems in general.

The objective of this research is the development of methods and software that will allow robots to detect and localize objects using Active Vision and develop descriptions of their visual appearance in terms of shape primitives. The approach is bio inspired and consists of three novel components. First, the robot will actively search the space of interest using an attention mechanism consisting of filters tuned to the appearance of objects. Second, an anthropomorphic segmentation mechanism will be used. The robot will fixate at a point within the attended area and segment the surface containing the fixation point, using contours and depth information from motion and stereo. Finally, a description of the segmented object, in terms of the contours of its visible surfaces and a qualitative description of their 3D shape will be developed. The intellectual merit of the proposed approach comes from the bio-inspired design and the interaction of visual learning with advanced behavior. The availability of filters will allow the triggering of contextual models that work in a top-down fashion meeting at some point the bottom-up low-level processes. Thus, the approach defines, for the first time, the meeting point where perception happens. The broader impacts of the proposed effort stem from the general usability of the proposed components. Adding top-down attention and segmentation capabilities to robots that can navigate and manipulate, will enable many technologies, for example household robots or assistive robots for the care of the elders, or robots in manufacturing, space exploration and education.

The objective of this research is the creation of a coastal observing system that enables dense, in situ, 4D sensing through networked, sensor-equipped underwater drifters. The approach is to develop the technologies required to deploy a swarm of autonomous buoyancy controlled drifters, which are vehicles that can control their depth, but are otherwise carried entirely by the ocean currents. Such Lagrangian sampling promises to deliver a wealth of new data, ranging from applications in physical oceanography (mapping 3D currents), biology (observing the dispersion of larvae and nutrients), environmental science (tracking coastal pollutants and effluents from storm drains), and security (monitoring harbors and ports). This observing system fundamentally requires accurate positions of the drifters (to interpret the spatial correlations of data samples), swarm control algorithms (to achieve desired sampling topologies), and wireless communication (to coordinate between the individual drifters). This research will create distributed techniques to self-localize the drifter swarm, novel swarm control algorithms that enable topology manipulation while purely leveraging the stratified flow environment, and efficient wireless underwater communication for information sharing. This project has significant societal impact and educational elements. Underwater drifter swarms will enable novel insights into a wide array of scientific questions, including understanding plankton transport, accumulation and dispersion as well as monitoring harmful algal blooms. Undergraduates will play an active role in many aspects of this project, thereby offering them a uniquely interdisciplinary experience. Finally, outreach to high school students will occur through the UCSD COSMOS summer program.

The objective of this research is to integrate user control with automated reflexes in the human-machine interface. The approach, taking inspiration from biology, analyzes control-switching issues in brain-computer interfaces. A nonhuman primate will perform a manual task while movement- and touch-related brain signals are recorded. While a robotic hand replays the movements, electronic signals will be recorded from touch sensors on the robot?s fingers, then mapped to touch-based brain signals, and used to give the subject tactile sensation via direct cortical stimulation. Context-dependent transfers of authority between the subject and reflex-like controls will be developed based on relationships between sensor signals and command signals. Issues of mixed authority and context awareness have general applicability in human-machine systems. This research advances methods for providing tactile feedback from a remote manipulator, dividing control appropriate to human and machine capabilities, and transferring authority in a smooth, context-dependent manner. These principles are essential to any cyber-physical system requiring robustness in the face of uncertainty, control delays, or limited information flow. The resulting transformative methods of human-machine communication and control will have applications for robotics (space, underwater, military, rescue, surgery, assistive, prosthetic), haptics, biomechanics, and neuroscience. Underrepresented undergraduates will be recruited from competitive university programs at Arizona State University and Mexico's Tec de Monterrey University. Outreach projects will engage the public and underrepresented school-aged children through interactive lab tours, instructional modules, and public lectures on robotics, human-machine systems, and social and ethical implications of neuroprostheses.

The goal of this project is to develop a novel cyber-physical system (CPS) for performing multimodal image-guided robot-assisted minimally invasive surgeries (MIS). The approach is based on: (1) novel quantitative analysis of multi-contrast data, (2) control that uses this information to maneuver conformable robotic manipulators, while adjusting on-the-fly scanning parameters to acquire additional information, and (3) human-information/machine-interfacing for comprehensive appreciation of the physical environment. The intellectual merit arises from the development of: (1) a CPS that relies on "real" and "real-time" data, minimizing parametric and abstracted assumptions, extracts and matures information from a dynamic physical system (patient and robot) by combining management of data collection (at the physical sensor site) and data analysis (at the cyber site), (2) "smart sensing", to control data acquisition based on disruptive or situation altering events, (3) control coordination by interlacing sensing, control and perception, and the incorporation of steerable tools. The societal impact arises from contributions to a leap in MIS: from "keyhole" visualization (i.e., laparoscopy) to in-situ real-time image guidance, thereby enabling a wider range of MIS. This will directly benefit patients and their families (faster recovery/reduced trauma). Economic impact arises from the cost-effectiveness of MIS to the health care system, faster patient return to the workplace, and technology commercialization. The project will integrate research and education, diversity and outreach, by enhancing current and introducing new research-intensive courses in Cyber-physical Systems, Medical Imaging and Medical Robotics, and dissemination via trans-institutional collaborations, a comprehensive web site, multimedia web-seminars, and distribution to high schools.