Towards Automated Sample Collection and Return in Extreme Underwater Environments

TL;DR

This paper demonstrates autonomous underwater robotic systems capable of sample collection and return in complex environments, serving as analogs for future extraterrestrial ocean exploration, with successful field trials in challenging settings.

Contribution

The paper introduces a hardware-independent computer vision architecture and control framework enabling high-level autonomous manipulation for marine robots in unstructured environments.

Findings

Successful autonomous biological sample collection in active undersea volcano

Effective 3D workspace understanding for manipulator planning

Demonstrated system robustness in challenging underwater environments

Abstract

In this report, we present the system design, operational strategy, and results of coordinated multi-vehicle field demonstrations of autonomous marine robotic technologies in search-for-life missions within the Pacific shelf margin of Costa Rica and the Santorini-Kolumbo caldera complex, which serve as analogs to environments that may exist in oceans beyond Earth. This report focuses on the automation of ROV manipulator operations for targeted biological sample-collection-and-return from the seafloor. In the context of future extraterrestrial exploration missions to ocean worlds, an ROV is an analog to a planetary lander, which must be capable of high-level autonomy. Our field trials involve two underwater vehicles, the SuBastian ROV and the Nereid Under Ice (NUI) hybrid ROV for mixed initiative (i.e., teleoperated or autonomous) missions, both equipped 7-DoF hydraulic manipulators. We describe an adaptable, hardware-independent computer vision architecture that enables high-level automated manipulation. The vision system provides a 3D understanding of the workspace to inform manipulator motion planning in complex unstructured environments. We demonstrate the effectiveness of the vision system and control framework through field trials in increasingly challenging environments, including the automated collection and return of biological samples from within the active undersea volcano, Kolumbo. Based on our experiences in the field, we discuss the performance of our system and identify promising directions for future research.