Paper Info
Title
Real-Time Underwater Onboard Vision Sensing System For Robotic Gripping
Abstract
In this study, a real-time underwater onboard vision sensing system is developed for robotic gripping. First, an efficient image enhancement method based on the Retinex theory is presented. The enhanced images are provided for underwater robot to observe the seabed environment clearly via cameras. Subsequently, a real-time lightweight object detector (RLOD) for the mobile embedded platform is proposed. The RLOD is designed as an hourglass detector network, which introduces dense connections and a featured pyramid network to improve the detection performance and speed. Moreover, from an engineering perspective, two merging methods are used to deploy the trained network. It can be implemented at 11.11 frames per second (FPS) on the Nvidia Jetson TX2 processor, satisfying the real-time requirement of underwater robotic gripping. Furthermore, a refraction tracing model is constructed. The comparative results show the effectiveness of the proposed methods. Finally, this onboard vision sensing system is mounted on an underwater robot with a manipulator to implement robotic gripping. Pool and sea experiments are conducted to verify the practicability of the developed system.
Year
DOI
Venue
2021
10.1109/TIM.2020.3028400
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Keywords
DocType
Volume
Real-time underwater vision sensing system, underwater object detection, underwater robotic gripping, underwater robots
Journal
70
ISSN
Citations 
PageRank 
0018-9456
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Yu Wang1399.08
Chong Tang284.88
Mingxue Cai331.77
Jiye Yin400.34
Shuo Wang528451.13
Long Cheng6149273.97
Rui Wang711122.06
Min Tan82342201.12