Session: 06-17-02 AI Technology for Ocean Engineering II

Paper Number: 123838

123838 - Preliminary Experimental Results of a Temporal Planning-Based System for Autonomous Inspection Using UGV 

Inspection and maintenance (IM) operations in offshore oil & gas platforms involve significant challenges due to the harsh conditions in such remote environments. Therefore, there is a need for robotic solutions that can accomplish IM missions autonomously, a goal that has become more feasible the last years due to advances in instrumentation, perception and artificial intelligence (AI). In this paper, we present initial experimental results of the Taurob unmanned ground vehicle (UGV) performing autonomous inspection at Equinor’s K-Lab Test Centre, located in Haugesund, Norway. The proposed solution employs the simultaneous task planning (STP) algorithm, introduced by Furelos-Blanco et al in 2018, as a high-level action planner. STP can take into account durative high-level actions, such as “visit a specific location”, “inspect a sensor”, or “take a picture of a specified component” and, in addition, can replan online in case of events such as low battery status, or the need to revisit a location. Communication with the robot is achieved via Equinor’s Integration and Supervisory Control of Autonomous Robots (ISAR) framework, which guarantees a fast and secure wi-fi connection. Two types of experiments were carried out: 1) A basic inspection round, which involves visiting a sequence of predefined waypoints; 2) A replanning scenario, which also takes into account the battery status. Our preliminary tests, where fast and efficient plans were computed and executed in real time, including replanning,  showed that connecting the guidance and control system of a UGV with a high-level planner like STP is a promising approach to increased autonomy in IM missions.

 

This paper presents the experimental results of the work presented in Hinostroza et al. (2023).
[1] M.A. Hinostroza, A.M. Lekkas, Aksel A. Transeth, B.Luteberget ,C. de Jonge , S. Sagatun (2023).  Automated Planning for Inspection and Maintenance operations using Unmanned Ground Vehicles. 22nd IFAC World Congress, Yokohama, Japan, 9– 14 July, 2023.

Presenting Author: Miguel Hinostroza Norwegian University of Science and Technology (NTNU)

Presenting Author Biography: Miguel Hinostroza has received the Ph.D. and M.Sc. degrees in Naval Architecture and Ocean Engineering from University of Lisbon, Portugal in 2021 and 2015, respectively.

He is currently a Researcher with the Department of Engineering Cybernetics, Norwegian University of Science and Technology, Norway. His current research interests include AI planning, dynamics, and control of autonomous robots, motion planning, guidance and control, experimental and model test with academic and industrial aerial, ground and maritime robots.

Authors:

Miguel Hinostroza Norwegian University of Science and Technology (NTNU)
Anastasios Lekkas Norwegian University of Science and Technology
Christian De Jonge Equinor, Norway
Svein Ivar Sagatun Equinor, Norway
Bjørnar Luteberget SINTEF Digital, Norway
Aksel Transeth SINTEF Digital, Norway