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Real-time computer vision and remote visual sensing platforms are increasingly used in numerous underwater applications such as shipwreck mapping, subsea inspection, coastal water monitoring, surveillance, coral reef surveying, invasive fish tracking, and more. Recent advancements in robot vision and powerful single-board computers have paved the way for an imminent revolution in the next generation of subsea technologies. In this chapter, we present these exciting emerging applications and discuss relevant open problems and practical considerations. First, we delineate the specific environmental and operational challenges of underwater vision and highlight some prominent scientific and engineering solutions to ensure robust visual perception. We specifically focus on the characteristics of underwater light propagation from the perspective of image formation and photometry. We also discuss the recent developments and trends in underwater imaging literature to facilitate the restoration, enhancement, and filtering of inherently noisy visual data. Subsequently, we demonstrate how these ideas are extended and deployed in the perception pipelines of Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs). In particular, we present several use cases for marine life monitoring and conservation, human-robot cooperative missions for inspecting submarine cables and archaeological sites, subsea structure or cave mapping, aquaculture, and marine ecology. We elaborately discuss how the deep visual learning and on-device AI breakthroughs are transforming the perception, planning, localization, and navigation capabilities of visually-guided underwater robots. Along this line, we also highlight the prospective future research directions and open problems at the intersection of computer vision and underwater robotics domains.
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Amphibious Bioinspired Robots for Ocean Objects Identification
Agility, robustness, endurance, and sustainability are the main challenges of the current distributed systems for ocean objects identification. Nowadays, developing a novel marine observation network to help identify threats and to provide both an early warning and data for forecasting models is a priority of marine missions. Autonomous systems, such as underwater robots and drones, can provide worthwhile information from the ocean environment; still, they have challenges associated with endurance, performance, and recovery. Skimming drones cannot be used to perform underwater missions, need a significant amount of energy to take off, and have stability problems due to the constant ocean wave motion. As for underwater swimming robots, they are generally slow and use a significant amount of energy. To this end, there is a need to design some novel bioinspired amphibious concepts that can overcome these challenges. In this paper, a network of distributed hybrid-amphibious robots with energy harvesting capabilities will be presented. This is accomplished through novel robot systems. The Lizard-Spider Octopus-Jellyfish-Rolling Robot (LSOJRR) is one of these novel ideas, which imitates the characteristics of a Golden wheel spider with rolling, jumping, and folding capabilities over the water, a Green Basilisk lizard with running capability over the water, and an octopus with unique underwater propulsion mechanism. The LSOJRR also has applications beyond Earth, and alternative designs of this robot are explored, particularly those involving the dispersal of swarms of smaller robots that also derive their design from biology. All of the designs presented in this paper draw inspiration from nature, and strive to achieve the goal of furthering the development for marine exploration.
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- Award ID(s):
- 1757793
- PAR ID:
- 10382428
- Date Published:
- Journal Name:
- AIAA SCITECH 2022 Forum
- Page Range / eLocation ID:
- 2781
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.2514/6.2021-2781
