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IJMERR 2023 Vol.12(2): 64-77
DOI: 10.18178/ijmerr.12.2.64-77

Autonomous Grasping Using Novel Distance Estimator

Martin Skaldebø1*, Bent A. Haugaløkken 2, and Ingrid Schjølberg 3
1. Department of Marine Technology, Norwegian University of Science and Technology, Trondheim, Norway
2. Department of Seafood Technology, SINTEF Ocean, Trondheim, Norway
3. Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim, Norway
*Correspondence: martin.b.skaldebo@ntnu.no

Manuscript received September 18, 2022; revised November 18, 2022; accepted December 30, 2022.

Abstract—This paper introduces a novel distance estimator using monocular vision for autonomous underwater grasping. The presented method is also applicable to topside grasping operations. The estimator is developed for robot manipulators with a monocular camera placed near the gripper. The fact that the camera is attached near the gripper makes it possible to design a method for capturing images from different positions, as the relative position change can be measured. The presented system can estimate relative distance to an object of unknown size with good precision. The manipulator applied in the presented work is the SeaArm-2, a fully electric underwater small modular manipulator. The manipulator is unique in its integrated monocular camera in the end-effector module, and its design facilitates the use of different end-effector tools. The camera is used for supervision, object detection, and tracking. The distance estimator was validated in a laboratory setting through autonomous grasping experiments. The manipulator was able to search for and find, estimate the relative distance of, grasp, and retrieve the relevant object in 12 out of 12 trials.

Keywords—object tracking, underwater manipulator, monocular vision, autonomous intervention

Cite: Martin Skaldebø, Bent A. Haugaløkken, and Ingrid Schjølberg, "Autonomous Grasping Using Novel Distance Estimator," International Journal of Mechanical Engineering and Robotics Research, Vol. 12, No. 2, pp. 64-77, March 2023. 

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.