Abstract: With nearly 10 million individuals carrying a diagnosis of Parkinson’s disease across the globe. Individuals with Parkinson’s disease experience tremors, rigidity, slowness of movement, and difficulties with walking and driving. Currently these individuals are required to attend weekly visits to the doctor's office for consistent reassessment regarding progression of the disease.

This is a collaborative research project between Washington University in St. Louis, Michigan State University and University of Nevada Reno and is investigating a cyber-physical framework for scalable, long-term monitoring and condition-based maintenance of civil infrastructures. Civil infrastructure constitutes a network of interdependent systems and utilities (e.g., highways, bridges, rail systems, buildings) that are necessary for supporting social and economic activities.

Within hazard and disaster response and recovery management, the National Incident Management System (NIMS) has become the dominant organizational model for incident response. The Incident Command System (ICS) provides report and operational templates that structure activities and resources during an incident or event. In an emergency situation, information can be sometimes contradictory and may even not be “clean”.

Abstract: This project is addressing how cyber physical walking systems (CPWS) can be designed to be safe, secure, and resilient despite a variety of unanticipated disturbances and how real-time dynamic control and behavior adaptation can be achieved in a diversity of environments.

Teams comprised of both humans and robots are increasingly becoming a reality. A key barrier to enabling teams fluently working together is that leadership roles of humans and robots are often determined a priori. In successful human-human teams, we find that leadership is an emergent behavior where team members can adaptively take, give up, or share leadership based on changing tasks or environments. To create human-robot teams capable of long-term interactions in dynamically changing environments, they need to be able to fluidly adapt leader and follower roles.

This proposal addresses the problem of spatial and temporal coverage for crowdsensing (CS). In particular, the approach focuses on the coverage of isolated sub-regions from the target area where participants' density is very low. We tackle this problem by persuading participants to modify their ongoing trajectories and visiting those regions before reaching their final destinations. We model a sensing market as a non-cooperative game, where participants are the players and trajectories are the strategies.