High-frequency Near-field Physeter macrocephalus Monitoring by Stereo-Autoencoder and 3D Model of Sonar Organ

International audiencePassive acoustics allow us to study large animals and obtain information that could not be gathered through other methods. In this paper we study a set of near-field audiovisual recordings of a sperm whale pod, acquired with a ultra high-frequency and small aperture antenna. We propose a novel kind of autoencoder, a Stereo-Autoencoder, and show how it allows to build acoustic manifolds in order to increase our knowledge regarding the characterization of their vocalizations, and possible acoustic individual signature

Efficient artifacts filter by density-based clustering in long term 3D whale passive acoustic monitoring with five hydrophones fixed under an Autonomous Surface Vehicle

International audiencePassive underwater acoustics allows for the monitoring of the echolocation clicks of cetaceans. Static hydrophone arrays monitor from a fixed location, however, they cannot track animals over long distances. More flexibility can be achieved by mounting hydrophones on a mobile structure. In this paper, we present the design of a small non-uniform array of five hydrophones mounted directly under the Autonomous Surface Vehicle (ASV) Sphyrna (also called an Autonomous Laboratory Vehicle) built by SeaProven in France. This configuration is made challenging by the 40cm aperture of the hydrophone array, extending only two meters below the surface and above the thermocline, thus presenting various artifacts. The array, fixed under the keel of the drone, is numerically stabilized in yaw and roll using the drone's Motion Processing Unit (MPU). To increase the accuracy of the 3D tracking computed from a four hour recording of a Sperm Whale diving several kilometers away, we propose an efficient joint filtering of the clicks in the Time Delay of Arrival (TDoA) space. We show how the DBSCAN algorithm efficiently removes any outlier detection among the thousands of transients, and yields to coherent high definition 3D tracks

REAL-TIME PASSIVE ACOUSTIC 3D TRACKING OF DEEP DIVING CETACEAN BY SMALL NON-UNIFORM MOBILE SURFACE ANTENNA

International audienceDetecting and localizing the echolocation clicks of sperm whales provides insight into their diving behavior, but existing methods are limited in range, imprecise, or costly. In this work, we demonstrate that we can obtain a high definition 3D track of deep diving cetaceans from a five-channel, small-aperture hydrophone array on a moving autonomous surface vehicle (ASV), enabled by the vessel's hydrodynamic quality and a high recording sample rate. Real-time processing is achieved by splitting our non-uniform array into two parts for time delay of arrival estimation. Resulting 3D tracks depict the behavior of the cetacean in the abyss (−1.2 km), with one position per second. This high resolution allows us to observe a correlation between the repetition rate of the predator's biosonar and the tortuosity of its track. Our proposed mobile observatory may offer new insights about whale behavior and its foraging success close to vessel traffic

Contextualized Monitoring in the Marine Environment

Marine mammal monitoring has seen improvements in the last few decades with advances made to both the monitoring hardware and post-processing computation methods. The addition of tag-based hydrophones, Fastloc GPS units, and an ever-increasing array of IMU sensors, coupled with the use of energetics proxies such as Overall Dynamic Body Acceleration (ODBA), has led to new insights into marine mammal swimming behavior that would not be possible using traditional secondary-observer methods. However, these advances have primarily been focused on and implemented in wild animal tracking, with less attention paid to the managed environment. This is a particularly important gap, as the cooperative nature of managed animals allows for research on swimming kinematics and energetics behavior with an intricacy that is difficult to achieve in the wild. While proxy-based methods are useful for relative inter-or-intra-animal comparisons, they are not robust enough for absolute energetics estimates for the animals, which can limit our understanding of their metabolic patterns. Proxies such as ODBA are based on filtered on-animal IMU data, and measure the aggregate high-pass acceleration as an estimate for the magnitude of the animal’s activity level at a given point in time. Depending on its body structure and locomotive gait, tag placement on the animal and the specific filtering techniques used can significantly impact the results. Any relation made to energetics is then strictly a mapping: a relation that may apply well to an individual or group under specific experimental conditions, but is not generalizable. To address this gap, this dissertation presents new tag-based hardware and data processing methods for persistently estimating cetacean swimming kinematics and energetics, which are functional in both managed and wild settings. Unfortunately, localization techniques for managed environments have not been thoroughly explored, so a new animal tracking method is required to spatially contextualize information on swimming behavior. State-of-the-art wild cetacean localization operates via sparse GPS updates upon animal surfacings, and can be paired with biologging-tag-based odometry for a continuous track. Such an approach is hindered by the structure and scale of managed environments: GPS suffers from increased error near and within buildings, and current odometry methods are insufficiently precise for habitat scales where locations of interest might be separated by meters, rather than kilometers (such as in the wild). There is then a need for a tracking method that uses an alternate source of absolute animal locations that can achieve the high precision necessary for meaningful results given the spatial scale. To this end, this dissertation presents a novel animal localization framework, based on tracking and sensor filtering techniques from the field of robotics that have been tailored for use in this setting. Overall, this research targets two main gaps: 1) the lack of persistent, absolute estimates of animal swimming energetics and kinematics, and 2) the lack of a robust, precise localization method for managed cetaceans. To address these gaps, the hardware and animal tracking methods developed to enable the rest of the dissertation are first defined. Next, a physics-based approach to directly monitor cetacean swimming energetics is both presented and implemented to study animal propulsion patterns under varying effort conditions. Finally, a high-fidelity 3D monitoring framework is introduced for tracking institutionally-managed cetaceans, and is applied alongside the energetics estimation method to provide a first look at the potential of spatially-contextualized animal monitoring.PHDRoboticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169756/1/gabaldon_1.pd