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CUREE: A Curious Underwater Robot for Ecosystem Exploration

Yogesh Girdhar, Nathan McGuire, Levi Cai, Stewart Jamieson, Seth McCammon, Brian Claus, John E. San Soucie, Jessica E. Todd, T. Aran Mooney

Abstract

The current approach to exploring and monitoring complex underwater ecosystems, such as coral reefs, is to conduct surveys using diver-held or static cameras, or deploying sensor buoys. These approaches often fail to capture the full variation and complexity of interactions between different reef organisms and their habitat. The CUREE platform presented in this paper provides a unique set of capabilities in the form of robot behaviors and perception algorithms to enable scientists to explore different aspects of an ecosystem. Examples of these capabilities include low-altitude visual surveys, soundscape surveys, habitat characterization, and animal following. We demonstrate these capabilities by describing two field deployments on coral reefs in the US Virgin Islands. In the first deployment, we show that CUREE can identify the preferred habitat type of snapping shrimp in a reef through a combination of a visual survey, habitat characterization, and a soundscape survey. In the second deployment, we demonstrate CUREE's ability to follow arbitrary animals by separately following a barracuda and stingray for several minutes each in midwater and benthic environments, respectively.

CUREE: A Curious Underwater Robot for Ecosystem Exploration

Abstract

The current approach to exploring and monitoring complex underwater ecosystems, such as coral reefs, is to conduct surveys using diver-held or static cameras, or deploying sensor buoys. These approaches often fail to capture the full variation and complexity of interactions between different reef organisms and their habitat. The CUREE platform presented in this paper provides a unique set of capabilities in the form of robot behaviors and perception algorithms to enable scientists to explore different aspects of an ecosystem. Examples of these capabilities include low-altitude visual surveys, soundscape surveys, habitat characterization, and animal following. We demonstrate these capabilities by describing two field deployments on coral reefs in the US Virgin Islands. In the first deployment, we show that CUREE can identify the preferred habitat type of snapping shrimp in a reef through a combination of a visual survey, habitat characterization, and a soundscape survey. In the second deployment, we demonstrate CUREE's ability to follow arbitrary animals by separately following a barracuda and stingray for several minutes each in midwater and benthic environments, respectively.
Paper Structure (11 sections, 7 equations, 8 figures)

This paper contains 11 sections, 7 equations, 8 figures.

Figures (8)

  • Figure 1: Illustration of CUREE conducting a reef survey. CUREE uses vision and passive acoustics to collect information about its environment. CuSA assists CUREE by providing a high-bandwidth communications link to scientists and improved localization of CUREE with GPS and USBL.
  • Figure 2: 3D reconstruction of Booby Rock Reef, St. John, USVI, produced from a CUREE visual survey. The AprilTag Olson2011 shown in the cutout is 20cm $\times$ 20cm, while the complete survey is approximately 20m $\times$ 20m.
  • Figure 3: CUREE's primary sensing capabilities come from forward and downward-looking stereo cameras and a four-channel hydrophone array (Photo credit: Austin Greene).
  • Figure 4: Sample Acoustic Survey conducted at Joel's Shoal Reef, US Virgin Islands. During drifting periods, there is no noise from the thrusters, allowing CUREE to detect sounds from marine animals, such as snapping shrimp.
  • Figure 5: CUREE is capable of conducting simultaneous visual and acoustic surveys over complex seafloor environments such as a coral reefs. The approach mixes low-altitude terrain and waypoint following behavior with drifting periods to capture soundscapes. In this survey of Joel's Shoal in the USVI, CUREE drifts for 10 seconds at every waypoint to enable soundscape observation at that location. Top: Spectrogram of audio observations at each waypoint and average observed snapping shrimp snap rate during the drifting window. Middle: Automatically computed visual topic labels representing different habitat types. Bottom: Examples of imagery captured by the cameras at different points of time. We see that images 2, 3, and 5 have similar topic distribution and correspond to a coral-covered habitats, whereas images 1 and 4 have similar topic distributions (but distinct from 2,3,5) and show sandy habitats. We see that Topic 3 (blue), which indicates the presence of dense corals in the images, correlates positively with high rates of snapping shrimp snaps.
  • ...and 3 more figures