Hai Lin, Ph.D. - US grants

Wireless sensor-actuator networks (WSAN) are systems consisting of numerous sensing and actuation devices that interact with the environment and coordinate their activities over a wireless communication network. This project studies "resilience" in WSANs. A resilient system is one that maintains an active awareness of surrounding threats and reacts to those threats in a manner that returns the system to operational normalcy in finite time. This project's approach to resilient WSANs rests on two fundamental trends. One trend uses machine-to-machine (M2M) communication networks that promise wireless networking with greater peak bit-rates and reliability than previously possible. The other trend comes from recent ideas that use quantization and event-triggered feedback in a unified manner to reduce bit rates required by real-time control systems. This project will evaluate and demonstrate this integrated control/communication approach to resilience on a multi-robotic testbed consisting of unmanned ground vehicles. The testbed will integrate M2M communication hardware/software with a multi-robot control architecture addressing task coordination and platform stabilization.

This project broadens its impact through organizations and programs on and around the Notre Dame campus that facilitate industrial engagement and technology transfer. The project will engage undergraduate and graduate students to support the project's testbed and algorithm development. The project will augment and re-organize Notre Dame's Cyber-Physical System (CPS) curriculum by integrating the results of this project into courses.

The objective of the proposal is to study cooperative tasking among teams of robots under uncertain environments. The research has four main objectives:
- To develop a formal theory of multi-robot cooperative tasking to guarantee given global specifications through explicitly designing local coordination. This study will address key issues such as control architectures, formal representations of tasks, task decomposition, decomposability, and modular tasking. Multidisciplinary approaches combining hybrid systems, supervisory control, and automata theory will be utilized.
- To further extend the theory to handle faults and uncertainty. This study will investigate the fault tolerant cooperative tasking from the perspectives of both passive fault tolerance and active fault tolerant control. The key issues, such as fault detection, characterization of tolerable fault patterns and dynamic reconfiguration, will be addressed from the hybrid and discrete event system theory point of view.
- To implement and demonstrate the design methods on real robotic systems. This empirical study will be conducted on a multi-robot testbed consisting of both autonomous unmanned ground and aerial vehicles. Prototype applications, such as a coordinated pollution detection and containment scenario, will be implemented to illustrate the effectiveness of the proposed approaches.
- To use effective pedagogy in teaching so as to promote learning and foster young talents in engineering.

Intellectual Merits: The proposed research addresses a fundamental question essential for advancements in swarming robotics, namely how to design local coordination among robots so as to achieve certain desired collective behaviors. This project seeks to develop and demonstrate a formal design theory for multi-robot cooperative tasking based on a variety of models and approaches from disciplines like control, computer sciences and robotics. The proposed theory will guarantee a given global performance from a team of swarming robots through designing their local coordination rules and control laws. Thus, the proposed method is of a top-down and correct-by-design nature. It therefore complements well the prevailing bottom-up design practices in swarming robotics, where the local interactions are usually predefined heuristically with inspirations from natural social behaviors.

Broader Impacts: The project has potential to provide a new perspective in tackling the complexity of large-scale distributed dynamical systems, such as sensor actuator networks, power grids and transportation systems. The study will help to advance our understanding of the relationship between emergent behaviors from a complex engineered system and local interactions among its distributed dynamical components. This understanding is critical to building more reliable and efficient future engineered systems. In particular, the theoretical and practical studies in this project may help swarming robotics to see more real applications, such as coordinated environment monitoring, emergency response, and law enforcement. Furthermore, undergraduate and graduate students will be engaged to support the project's testbed and algorithm developments.

Driven by both civilian and military applications, such as coordinated surveillance, search and rescue, underwater or space exploration, manipulation in hazardous environments, and rapid emergency response, cooperative actions by teams of robots has emerged as an important research area. However, the coordination strategies for such robot teams are still developed to a great extent by trial-and-error processes. Hence, the strategies cannot guarantee mission success. This award supports fundamental research to provide a provably correct formal design theory of multi-robot systems that guarantees mission success. Furthermore, results from the research can be extended to the design of more general cyber-physical systems (CPSs) consisting of distributed and coordinated subsystems, such as the national power grid, ground/air traffic networks, and manufacturing systems. These CPSs are critical components of the national civil infrastructure that must operate reliably to ensure public safety. The multidisciplinary approach taken will help broaden participation of underrepresented groups in research and positively impact engineering education.

Focusing on multi-robot teams, the goal of the research is to build foundations for a provably correct formal design theory for CPSs. This design theory will guarantee a given global performance of multi-robot teams through designing local coordination rules and control laws. The basic idea is to decompose the team mission into individual subtasks such that the design can be reduced to a local synthesis problem for individual robots. Multidisciplinary approaches combining hybrid systems, supervisory control, regular inference and model checking will be utilized to achieve this goal. The developed theory will enable robots in the team to cooperatively learn their individual roles in a mission, and then automatically synthesize local supervisors to fulfill their subtasks. A salient feature of this method lies on its ability to handle environmental uncertainties and unmodeled dynamics, as there is no need for an explicit model of the transition dynamics of each agent/robot and their interactions with the environment. In addition, the design is online and reactive, enabling the robot team to adapt to changing environments and dynamic tasking. The derived theory will be implemented as software tools and will be demonstrated through real robotic systems consisting of unmanned ground and aerial vehicles in unstructured urban/rural areas.

Future space missions will increasingly rely on autonomous robots like the NASA Valkyrie human-centered robot for deploying equipment, assisting astronauts, and maintaining facilities in real world partially-observable and cluttered environments. Despite significant progress in robotic mobility, manipulation, and perception, there has been relatively little progress on providing formal performance guarantees for these integrated systems. Formal guarantees are critical for achieving long term autonomy, particularly for robots performing complex tasks requiring successful execution of multiple component subtasks. Thus, the goal of this project is to develop performance guarantees for space robots operating in unstructured real world environments. Although robots are used as design examples, the project is of a basic research nature and the results can have impacts on other fields, such as sensor/actuator networks, manufacturing and transportation systems. The multidisciplinary approach taken for this project will help broaden participation of underrepresented groups and positively impact engineering and computer science education.

The objective of this project is to develop new methods to synthesize coordinated manipulation and locomotion plans and control policies that verifiably adhere to formal mission specifications. There are two major thrusts. First, the PIs plan to develop manipulation, locomotion, and motion primitives that can provide performance guarantees in unstructured, partially observable, and dynamic environments. The focus will be on using methods from perception and planning under uncertainty to provide guarantees in cluttered and partially observable environments. The PIs will also leverage new tools from hybrid systems and sampling based methods to achieve controllers with verifiable guarantees through contact mode switches. Second, the PIs plan to devise methods to automatically synthesize mission plans in a way that can guarantee the accomplishment of high-level mission goals or bound the probability of failure. The focus will be on automatic and learning-based design, enabling the system to adapt to changing environments, uncertain faults and potential adversaries. Most of the work performed under this project will be demonstrated in the context of complex space tasks inspired by NASA scenarios.

Many emergencies require people to evacuate a building quickly. During an emergency, evacuees must make quick decisions, so they tend to rely on default decision making that may put them at risk, such as exiting the way they entered, following a crowd, or sheltering in place. When a crowd attempts to exit through a single exit, choke points and crowd congestion may impede the safe flow of evacuees, potentially resulting in a stampede of people and the loss of human lives. Mobile robots are increasingly being deployed as assistants on city streets and in hotels, shopping centers and hospitals. The future ubiquity of these systems offers an opportunity to change how people are evacuated from dangerous situations. In particular, when compared with traditional emergency infrastructure, such as fire alarms and smoke detectors, mobile robots can achieve better situation awareness and use this information to expedite evacuation and enhance safety. Additionally, mobile robots can be used in risky and life-threatening situations, such as chemical spills or active shooter scenarios, which present dangers to human first responders.

This project aims to derive a scalable design framework and develop an embodied multi-robot evacuation system where multiple mobile robots, originally tasked for different purposes, serve as emergency evacuation first responders leading people to safety. In particular, multiple mobile robots efficiently coordinate with each other and actively interact with evacuees to maximize their egress. The project significantly contributes to the understanding of how people respond to a robots' directions and authoritative commands. Furthermore, the project implements these findings and demonstrates their effectiveness using real-world experiments with human subjects. Beyond emergency evacuation, the research findings can be extended to many other related areas, especially those involving cooperative robot teams that are embodied in an uncertain and dynamic physical world with the need to actively interact with humans; e.g., battlefield, law enforcement, urban transportation systems, manufacturing systems, rehabilitation and health management.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Human-robot collaboration technologies aim to combine the strengths from humans with those of robots. Robots excel at handling repeated routines with much higher precision and speed, and longer endurance. Humans, on the other hand, have superior perception capabilities and are much better in face of uncertainties and unexpected situations. For example, a scratch on a transparent glass can be easily detected by human eyes but presents an extremely hard challenge for computer vision. Finding principles to help design effective collaboration between humans and robots (or humans and computers in general) is core to advances in cyber-human systems. In addition, many cyber-human system applications, such as joint assembly manufacturing, driver assistance, and robot-assisted surgery are safety critical and need to achieve complex high-level tasks with guaranteed performance. This project aims to derive a provably-correct human-robot collaboration design theory that can guarantee the accomplishment of high-level complex missions. Research from this project can benefit society by increasing the safety and trustworthiness in the many real-world applications involving human-robot and human-computer collaborations such as service robots, automated manufacturing systems, emergency responses, and exploration of unknown spaces.

This project adopts a new model, called vector auto-regressive partially observable Markov decision process (VAR-POMDP), to manage uncertainties, and it uses non-parametric Bayesian methods to learn the model from data. With the learned model, an automatic high-level task planning in human-robot collaboration with respect to formal specifications is studied. The team of researchers will further study how to achieve online (real-time) adaptations of the overall system when robots are interacting with different individuals or facing uncertain environments. Beyond theoretical studies, the team will develop software tools and evaluate the effectiveness of the design theory through a real robotic test-bed.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.