Abstract
The demand for autonomous robotic solutions capable of operating in complex and dangerous environments – such as those found in inspection and maintenance (I&M) operations – is growing. However, the success of autonomous system deployments relies heavily on their actual and human-perceived safety. Current AI-based predictions often lack robust uncertainty handling, which could lead to catastrophic outcomes.In the SAFESUB project, we address this gap by developing a framework for reliable uncertainty estimation and control throughout a sensing, perception, and control pipeline for autonomous uncrewed underwater vehicle (UUV) interventions.In this paper, we present the overall SAFESUB concept, detail relevant opportunities (use cases) and research challenges for future autonomous UUV intervention in I&M operations, and outline our preliminary results and next steps for the SAFESUB concept components: 1) A novel 3D underwater camera system with built-in uncertainty estimation of sensor data, 2) a basis for perception for 6-DOF pose estimation and corresponding uncertainty, and 3) an uncertainty-aware UUV intervention architecture designed for risk reduction in operations. The components are under development, and details will be shared in subsequent component-specific papers as the purpose of this paper is to give a project-wide overview and promptly share the SAFESUB concept. The paper also explores the state of the art on underwater sensing, perception, and intervention techniques, and provides a categorization of UUV operation concepts.
