Autonomous Subsea Cable Search and Tracking with Graph-Optimised Priors and Visual Tracking

Global communications rely on subsea cable infrastructure that remains vulnerable to damage from natural hazards and human activity. Autonomous underwater vehicles (AUVs) offer an efficient means to inspect long sections of exposed cable, but uncertainty in cable route maps, small cable diameters and partial burial makes continuous tracking a challenge. This paper presents a novel cable search and tracking method that leverages uncertain prior cable route maps. Graph-based optimisation continuously update the cable route to remain consistent with visual observations. Route uncertainty is constrained as a function of distance from observations using physics-based catenary models that account for cable parameters (i.e., lay depth, diameter, and density), bounding the search space to physically feasible regions and improving search efficiency. Cable detection is performed using a semi-supervised classifier running in real-time on-board a camera-equipped AUV. These detections both update the graph-based optimisation and enable visual cable tracking. When tracking is lost due to misclassification, burial or imperfect control, the bounded search space enables efficient recovery. The approach was demonstrated in field trials using the University of Southampton's Smarty200 AUV. The system successfully located the cable despite deliberate errors in it initial cable route map, updating this to be consistent with observations and using visual tracking to inspect up to 59% of a 120m test cable, with successful recovered after tracking loss.

Industry Led Use-Case Development for Human-Swarm Operations

In the domain of unmanned vehicles, autonomous robotic swarms promise to deliver increased efficiency and collective autonomy. How these swarms will operate in the future, and what communication requirements and operational boundaries will arise are yet to be sufficiently defined. A workshop was conducted with 11 professional unmanned-vehicle operators and designers with the objective of identifying use-cases for developing and testing robotic swarms. Three scenarios were defined by experts and were then compiled to produce a single use case outlining the scenario, objectives, agents, communication requirements and stages of operation when collaborating with highly autonomous swarms. Our compiled use case is intended for researchers, designers, and manufacturers alike to test and tailor their design pipeline to accommodate for some of the key issues in human-swarm ininteraction. Examples of application include informing simulation development, forming the basis of further design workshops, and identifying trust issues that may arise between human operators and the swarm.