Considered is a class of cooperative control problems that has a special affine characterization. Included in this class of multi-agent problems are the so called radar deception problem, formation keeping and formation reconfiguration. An intrinsic geometric formulation of the associated constraints unifies this class of problems and it is the first time such a generalization has been presented. Based on this geometric formulation, a real-time motion planning algorithm is proposed to generate dynamically feasible reference trajectories for the class. The proposed approach explicitly considers actuator and operating constraints of the individual agents and constrained dynamics are derived intrinsically for the multi-agent system which makes these constraints transparent. Deriving the constrained dynamics eliminates the need for nonlinear programming to account for the system constraints, making the approach amenable to real-time control. Explicit consideration of actuator and operating limitations and nonholonomic constraints in the design of the reference trajectories addresses the important issue of dynamic feasibility. The motion planning algorithm developed here is verified through simulations for the radar deception, rigid formation keeping and formation reconfiguration problems. A key objective of this study is to advocate a change in paradigm in the approach to formation control by addressing the key issues of dynamic feasibility and computational complexity. The other important contributions of this study are: Unifying formulation of constrained dynamics for a class of problems in formation control through the intrinsic geometry of their nonholonomic and holonomic constraints; Deriving these constrained dynamics in any choice of frame that can even be coordinate free; Explicit consideration of actuator and operating limits in formation control to design dynamically feasible reference trajectories and Developing a real-time, distributed, scalable motion planning algorithm applicable to a class of autonomous multi-agent systems in formation control.

Public transportation provides people with access to education, employment, health and community activities. However, navigating inside public hubs for people with disabilities such as cognitive or mobility impairments can be very challenging and dangerous. With the rapid development of digital technology such as Smartphones and sensors, there are unprecedented opportunities to assist people with disabilities to conquer these challenges. In this research, we aim to create a two-step indoor navigation solution for users with different mobility and orientation abilities. In the first step, we developed a virtual reality-based pre-travel training module that enables users to familiarize themselves with the virtual environment which represents the physical environment. After users feel confident and familiar enough with the environment, they proceed to the second step in which they visit the physical environment and use our real-time navigation assistance module. The pre-travel training module is developed using a Unity-based 3D game and includes a virtual indoor environment that represents the physical environment. The game provides a navigation function that highlights the path between the user location and the chosen destination. Considering the unique needs of cognitive impaired users, we designed action training modules in the game environment which train the user to use the ticket machine, fare gate and call boxes. Such training modules help cognitive impaired users familiarize themselves with the environment as well as gain confidence to experience the physical environment. When the users are ready to visit the physical environment, they use our real-time navigation assistance module which includes the same 3D virtual environment developed for the pre-travel training module. This approach is particularly important for people with cognitive impairment since they cannot organize navigation cues effectively. Using the Bluetooth Low Energy (BLE) infrastructure in the environment, our localization algorithm can track the user location in real-time. Subsequently, the user’s location will be integrated into the game environment so that the navigation path between the user’s current location and the selected destination can be generated and visualized by the user on the fly.