Development of an Inexpensive Decentralized Autonomous Aquatic Craft Swarm System for Ocean Exploration

Abstract

Swarm robotics in maritime engineering is a promising approach characterized by large numbers of relatively small and inexpensive autonomous aquatic crafts (AACs) to monitor marine environments. Compared with a single, large aquatic manned or unmanned surface vehicle, a highly distributed aquatic swarm system with several AACs features advantages in numerous real-world maritime missions, and its natural potential is qualified for new classes of tasks that uniformly feature low cost and high efficiency through time. This article develops an inexpensive AAC based on an embedded-system companion computer and open-source autopilot, providing a verification platform for education and research on swarm algorithm on water surfaces. A topology communication network, including an inner communication network to exchange information among AACs and an external communication network for monitoring the state of the AAC Swarm System (AACSS), was designed based on the topology built into the Xbee units for the AACSS. In the emergence control network, the transmitter and receiver were coupled to distribute or recover the AAC. The swarm motion behaviors in AAC were resolved into the capabilities of go-to-waypoint and path following, which can be accomplished by two uncoupled controllers: speed controller and heading controller. The good performance of velocity and heading controllers in go-to-waypoint was proven in a series of simulations. Path following was achieved by tracking a set of ordered waypoints in the go-to-waypoint. Finally, a sea trial conducted at the China National Deep Sea Center successfully demonstrated the motion capability of the AAC. The sea trial results showed that the AAC is suited to carry out environmental monitoring tasks by efficiently covering the desired path, allowing for redundancy in the data collection process and tolerating the individual AACs’ path-following offset caused by winds and waves.

Keywords

Marine environment monitoring / Swarm robotics / Autonomous aquatic craft / Unmanned surface vehicles / Autonomous aquatic craft swarm system / Decentralized control