Allowing untrained scientists to safely pilot ROVs: Early collision detection and avoidance using omnidirectional vision

Abstract

The study of underwater environments involves multiple hazards that can compromise the safety of robots. Underwater missions require a high level of attention from Remotely Operated Vehicle (ROV) operators to avoid damage to the robot. For this reason, there is a growing trend in research to develop systems with new capabilities, such as advanced assisted mapping, spatial awareness and safety, and user immersion. The aim of this work is to devise a system that provides the vehicle with proximity awareness capabilities for navigation in complex environments. By using the advantages of omnidirectional multi-camera systems, a much higher level of spatial awareness can be achieved. This paper presents a visual-based multi-camera system which is able to detect the presence of nearby objects in the environment, to create a local map of points, and to assign collision risk values to this map. The system exploits this information to generate warnings when approaching potentially dangerous obstacles and at the same time creates a collision risk map that provides a proximity awareness representation of the environment.