In conventional design processes, the design of the plant, the con- troller, the prototype as well as the certification of validity are products of consecutive phases of development utilizing distinct simulation, fabrication, and synthesis tools. Each phase produces an “optimal” solution, which is typically not jointly optimal for all phases. Phases need to be restarted from scratch if a new edge case or catastrophic failure is discovered at a later stage, and the interaction between failures, fabrication tolerances, and model inaccuracy is murky at best. To overcome these issues, and building from our effort as part of a current AFOSR grant, we propose to build a test bed implementing a coherent and provably rational methodology for automated design optimization, modeling, test and evaluation, and validation of autonomous systems with guaranteed levels of risk and robustness to uncertainty. The test bed will permit prototyping, experimentation, and redesign of autonomous systems and their components in an unified system. No such test bed is known yet to exist.

The proposed Center of Excellence will pioneer the development of fundamental theories and methods to enable assured autonomous mission execution in complex, uncertain, and adversarial conditions. Our vision is that assured autonomous operations by a network of agents in contested environments require an integrated focus on the complex union of both physical and information dynamics within the analysis, design, and synthesis of logical decision making and control design. Efforts will focus on the availability, integrity, and effective use of information by leveraging our team’s diverse toolsets in dynamics, mathematics, control theory, information theory, communications, and computer science. Networks of autonomous systems will require information exchanges of many data types, including high-level mission specifications and sensor feedback for navigation and control. The goal of assuring autonomy is complicated by the interplay between dynamics of autonomous agents and the stochastic and intermittent dynamics of network traffic. This challenge is further amplified by delays and asynchrony in information flows. Information perturbations can also emanate from adversarial actors in unique and complex ways, requiring security-aware design and analysis methods. For example, we will develop techniques to protect mission-critical information and prevent information disruption/corruption. These challenges must be addressed considering resource limitations and quantitative tradeoffs.

The objective of this work is to generate new fundamental science for cyber-physical systems (CPSs) that enables more accurate and faster trajectory synthesis for controllers with nonlinear plants, or nonlinear constraints that encode obstacles. The approach is to utilize hybrid control to switch between models whose accuracy is normalized by their computational burden. This synergistic approach is why we deem our proposed work will enable Computationally Aware Cyber-Physical Systems. The results from this project will advance the knowledge on modeling, analysis, and design of CPSs that utilize predictive methods for trajectory synthesis under constraints. Current algorithm designs seldom include the computational limitations of the hardware/software on which they are implemented as explicit constraints; thus, a challenge is to correctly approximate (or account for) how these constraints can be overcome for real-time systems. The results will include methods for the design of algorithms that adapt to the computational limitations of autonomous and semi-autonomous systems that must satisfy stringent timing and safety requirements. For this purpose, we propose tools capable of accounting for computational capabilities in real-time, and hybrid feedback algorithms that include prediction schemes exploiting computational capabilities to arrive at more accurate predictions, within the time constraints. The problem space will draw from models of Unmanned Air Systems (UAS) in the National Air Space (NAS); algorithms will be modeled in terms of hybrid dynamical systems, to guarantee dynamical properties of interest.

The Slugbotics research team is completing an ROV to compete in the annual MATE (Marine Advanced Technology Education) competition at the Explorer level. The objectives and goals of this competition change yearly, requiring a new ROV to be built, providing a chance for constant innovation and improvement. The 2018 competition is held in the Seattle area and is themed around the work that professional ROVs perform in the local area, such as the recovery of airplane wreckage from the bottom of Lake Washington, installing tidal turbine equipment, and gathering seismic earthquake activity using an ocean bottom sensor. 

Slugbotics is a student organization at UC Santa Cruz focused on introducing students to underwater robotics. They design, program, fabricate, and test ROVs (Remote Operated Vehicles) that are designed to complete complex tasks in a marine environment. In addition to the MATE competition, Slugbotics also serves as a community education and outreach group. They assist with the organization and running of the Monterey/Watsonville MATE regional, showing younger teams what a college level ROV looks like and giving them possibilities for their future builds.