Marine cabled video-observatories allow the non-destructive sampling of species at frequencies and durations that have never been attained before Nevertheless, the lack of appropriate methods to automatically process video imagery limits this technology for the purposes of ecosystem monitoring Automation is a prerequisite to deal with the huge quantities of video footage captured by cameras, which can then transform these devices into true autonomous sensors In this study, we have developed a novel methodology that is based on genetic programming for content-based image analysis Our aim was to capture the temporal dynamics of fish abundance We processed more than 20,000 images that were acquired in a challenging real-world coastal scenario at the OBSEA-EMSO testing-site The images were collected at 30-min frequency, continuously for two years, over day and night The highly variable environmental conditions allowed us to test the effectiveness of our approach under changing light radiation, water turbidity, background confusion, and bio-fouling growth on the camera housing The automated recognition results were highly correlated with the manual counts and they were highly reliable when used to track fish variations at different hourly, daily, and monthly time scales In addition, our methodology could be easily transferred to other cabled video-observatories

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Tracking Fish Abundance by Underwater Image Recognition

It is a challengeable task to plan multi-objective optimization paths for autonomous underwater vehicles (AUVs) in an unknown environments, which involves reducing travel time, shortening path length, keeping navigation safety, and smoothing trajectory. To address the above challenges, a real-time path planning approach combining particle swarm optimization and waypoint guidance is proposed for AUV in unknown oceanic environments in this paper. In this algorithm, a multi-beam forward looking sonar (FLS) is utilized to detect obstacles and the output data of FLS are used to produce those obstacles' outlines (polygons). Particle swarm optimization is used to search for appropriate temporary waypoints, in which the optimization parameters of path planning are taken into account. Subsequently, an optimal path is automatically generated under the guidance of the destination and these temporary waypoints. Finally, three algorithms, including artificial potential field and genic algorithm, are adopted in the simulation experiments. The simulation results show that the proposed algorithm can generate the optimal paths compared with the other two algorithms.

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A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance

A comprehensive review and proposed architecture for offshore power system

The exploration of oceans using autonomous underwater vehicles (AUVs) is necessary for activities, such as the sustainable management of fishery resources, extraction of seafloor minerals and energy resources, and inspection of underwater infrastructure. As the next step in ocean exploration, AUVs are expected to employ end-effectors to make physical contact with seafloor creatures and materials. We propose a scenario for realizing a sampling mission using an AUV that is equipped to sample marine life. In this scenario, the sampling AUV observes the seafloor while concurrently transmitting the observed images to a surface vessel for inspection by the AUV operators. If the received images show an object of interest, the object is selected as a candidate of sampling target by the operators, who send a sampling command to the AUV. After receiving the command, the AUV returns to the target area and attempts to sample it. In this paper, we propose a system for transmitting images of the seafloor as part of the sampling-mission scenario. The proposed image transmission system includes a process for enhancing images of the deep seafloor, a process for selecting interesting images, and processes for compressing and reconstructing images. The image enhancement process resolves imaging problems resulting from light attenuation, such as color attenuation and uneven illumination. The process for selecting interesting images selects those that contain interesting objects, such as marine life. The selection process prevents the transmission of meaningless images that contain only flat sand on the seafloor. The proposed image compression method, which is based on color depth compression, reduces the amount of data. The combined process of selecting an interesting image and compressing it reduces various problems in acoustic communication, such as low information density and data loss. Instead of an overall image, part of an overall image is transmitted by a set of data packet, and each received data packet is reconstructed onboard the vessel. Because of image compression, the colors of a reconstructed image differ from those of an enhanced image. However, the reconstructed image contains similar colors, and the structural similarity index was found to be 91.4% by evaluating images that were subjected to a 4-b color compression. The proposed image transmission system was tested in the Sea of Okhotsk, and these tests were performed four times in different sea areas (minimum depth 380 m, maximum depth 590 m). The results show that the size of the data for a single image was reduced by a factor of 18 using the proposed image compression process, with each image taking 3.7 s to be transmitted via an acoustic modem (20 kb/s). Of the automatically selected images, 63% contained marine life, and the total transmission success rate was 22%.

An Optical Image Transmission System for Deep Sea Creature Sampling Missions Using Autonomous Underwater Vehicle

This letter reports the sea experiments of a navigation method for multiple autonomous underwater vehicles (AUVs) that relies on a single high-performance AUV, which can estimate its self-state (position and pose) accurately without any support. In the method, there is a parent AUV and child AUVs. While the latter have minimal navigational sensors, such as a microelectromechanical gyro, a single-axis fiber optic gyro and cameras, the former can estimate its self-state without any support using high-grade navigational sensors, such as an inertial navigation system and a Doppler velocity log. As all the AUVs have acoustic positioning and communication devices, the child AUVs can also estimate their self-state as accurately as the parent AUV; thanks to relative positioning with the parent AUV. We performed the sea experiments in a hydrothermal vent field using AUVs. Post-processing state estimation using sensor data from the experiments showed that the proposed method can realize long-distance navigation while maintaining an accuracy more than five times that for navigation independently performed by a child AUV.

Accurate and Efficient Seafloor Observations With Multiple Autonomous Underwater Vehicles: Theory and Experiments in a Hydrothermal Vent Field

This paper describes the design of a newly-developed Autonomous Underwater Vehicle “HOBALIN” by National Maritime Research Institute, Japan. The major mission of the AUV is to explore hydrothermal vents by taking photographs hovering over the seafloor at an altitude of 2–5 meters, up to 2,000 meters depth. “HOBALIN” was developed as a practical AUV based on the design of the AUV “TUNA-SAND”. Therefore, rapid construction and deployment was achieved. Moreover, as the AUV is a small-sized system, it is easy to handle on any type of support ship which doesn't have any specialized facility for AUVs. Several trial dives were conducted to confirm the validity of the system in Suruga Bay. “HOBALIN” dived and traveled along the predefined survey lines and took seafloor pictures.

Development of hovering-type AUV “HOBALIN” for exploring seafloor hydrothermal deposits

Expensive kichiji rockfish is important catch for fishers and decreas significantly by over fishing. Common investigation method by the trawl for the fish is difficult to survey on rough terrain and need for big support of the ship. This paper proposes resource investigation method for kichiji rockfish using autonomous underwater vehicle (AUV) Tuna-Sand, and image processing method for precise measurement of the fish length. The AUV Tuna-Sand was developed for survey of material and energy resources in deep-sea such, and can observe natural seafloor automatically using only mounted sensors and devices. Our image processing makes a photograph possible to measure accurately the fish length by color correction for removing the unevenness of the brightness and distortion correction. The AUV Tuna-Sand surveyed for 24 hours in Kitami-Yamato Bank off Northern Japan. The vehicle took about 5,300 pictures of the seafloor during five dives in the bank. 37 kichiji rockfish of about 90 to 340 mm long were in all photographs. The survey results showed the fish of 150 to 200 mm long was most often found in all dives although the number of the othSer long was not many. Six mosaic images made by our method showed that all kichiji rockfish stay on the seafloor by oneself without swam and the shortest distance between kichiji rockfish was 4.0 m.

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Resource investigation for Kichiji rockfish by autonomous underwater vehicle in Kitami-Yamato bank off Northern Japan

A new autonomous surface vehicle (ASV) has been developed for control of multiple autonomous underwater vehicles (AUVs). Because it is semi-submersible type, the attitude in the sea surface waves is stable though the size is smaller than typical ASV. The cruising speed (3 kt) is confirmed in the testing basin. The operational concepts for control of multiple AUVs are discussed.

Development of a semi-submersible autonomous surface vehicle for control of multiple autonomous underwater vehicles

A new complex system of underwater positioning and communication has been developed for control of multiple autonomous underwater vehicles (AUVs). It consists of a semi-submersible autonomous surface vehicle (ASV), a hovering type AUV, and three surface buoys. The operational concepts for control of multiple AUVs are discussed.

Development of a regional underwater positioning and communication system for control of multiple autonomous underwater vehicles

Autonomouse underwater vehicles(AUVs) are vital tools for detailed ocean survey in recent years. Amongst them, hovering-type AUVs are specialized in optical observation using cameras and travel near the seafloor avoiding obstacles. Therefore, it is important to maintain proper distance between AUV and objects which should be approached to take pictures.

Shogo Inaba

Papers

Development of hovering-type AUV “HOBALIN” for exploring seafloor hydrothermal deposits

Resource investigation for Kichiji rockfish by autonomous underwater vehicle in Kitami-Yamato bank off Northern Japan

Development of a semi-submersible autonomous surface vehicle for control of multiple autonomous underwater vehicles

Development of a regional underwater positioning and communication system for control of multiple autonomous underwater vehicles

Obstacle avoidance method appropriate for the steep terrain of the deep seafloor