CPS:Synergy:Collaborative Research:Towards Effective and Efficient Sensing-Motion Co-Design of Swarming Cyber-Physical Systems

The overall research objective of the project is to establish and demonstrate a generic motion- sensing co-design procedure that significantly reduces the complexity of mission design for swarm- ing CPS, and greatly facilitates the development of effective and efficient control and sensing strategies. The objective of the project will be achieved through the integration of three main com- ponents: the design of cooperative control and sensing strategies, the development of Magnetic- induction-based underwater communication and localization technique, and the design of smart- material actuated biorobotic fish.

Source seeking is one of the fundamental and representative missions for swarming CPS with a wide range of practical applications. In the past year, we have (1) proposed a cooperative filtering scheme to achieve online parameter identification and source seeking of spatial-temporal varying fields using a swarming CPS; and (2) built a controllable CO2 diffusion field and constructed a static CO2 sensor network to measure and calibrate the field so that the proposed algorithms can be validated in realistic fields. This year, we (1) conducted experiments using four Khepera IV robots equipped with CO2 sensors in the realistic diffusion field to perform online parameter identification and source seeking; (2) extended the the proposed online parameter identification and source seeking strategy to take into account the cases that there are obstacles and hazard zones in the field that the robots should avoid; and (3) verified the algorithms in the realistic diffusion field pre-collected by a static sensor network.

Collision avoidance is an important requirement in vehicle swarms. In our project, we employ the collision cone approach. The collision cone approach has several advantages over other approaches (such as potential fields, navigation functions, RRTs, etc.) in that it is a reactive, on- line technique suitable for dynamic environments, and possesses strong analytical foundations. We have developed cooperative collision avoidance laws with formation control for objects with heterogeneous shape. The simulation comprises of four robotic fish with heterogeneous shapes, whose initial positions and velocities are such that they are on a collision course to each other. The four robotic fish come out of their respective collision cones, and eventually form a square formation, as desired. We have also integrated the collision avoidance laws with the dynamics of a hybrid-tailed robotic fish as well as the source seeking laws.

To provide an enabling mobile platform to verify the proposed strategies, we have developed a 2D maneuverable robotic fish propelled by servo/IPMC hybrid tails. We have built a prototype of the robotic fish and tested it in a water tank. We have derived the body dynamics, the thrust and drag forces, the hybrid tail model, and the IPMC joint model. The model is verified via experiments. To allow robotic fish to exchange messages with reliably controllable performance in the harsh underwater environment, we develop novel Magnetic Induction (MI)-based underwater communi- cation module. The contribution of this project in the past year focus on (1) developing an analyt- ical channel model for MI underwater communication to characterize the complex underwater MI channels, especially in the shallow water with omnidirectional antennas; and (2) developing and implementing the environment-aware and MI-based localization technique. The new contribution of this project include (1) comprehensive understanding of MI underwater channel characteris- tics; (2) design and implementation of MI underwater transceivers using 3D coil antennas; and (3) design and implementation of MI underwater localization system.