Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

A Study of the Hydrostatic and Hydrodynamic Properties of Aeoliscus Straigatus

Aeoliscus strigatus is a highly maneuverable fish found in the Indo-Pacific region. It boasts a unique head down posture and employs median paired fin propulsion to perform precise movements. The need for highly maneuverable underwater AUVs for exploration and testing drove the examination of the hydrostatics and hydrodynamics influencing Aeoliscus. To determine the stability of Aeoliscus the center of gravity and buoyancy were found. Center of gravity was experimentally located using the three plumb line method while center of buoyancy was located using two separate methods. The first method utilized the measured buoyant force, a rigidly mounted fish and a tank of water raised to displace ½ of the buoyant force. Method two utilized a microcomputed tomography (micro-CT) system to create a 3D model of the fish and allowed for computational location of the center of buoyancy. The average normalized approximation of the center of gravity was found to be 0.46 posterior to the mouth and 0.34 ventral to the leading dorsal edge of the fish. The average normalized approximation of the center of buoyancy was found to be 0.46 and 0.45 posterior to the mouth and 0.35 and 0.43 ventral to the leading dorsal edge of the fish by the micro-CT system and the experimental method respectively. Velocity, Reynold’s number and coefficient of drag were found to as a first step to understanding the hydrodynamics of Aeoliscus. The maximum observed velocity was 300 mm/s or about 22 body lengths per second, a Reynolds number of 4222, indicating laminar flow and a coefficient of drag of 0.029, which is similar to that of other fish

Multiple Fish Tracking via Viterbi Data Association for Low-Frame-Rate Underwater Camera Systems †

Abstract-Non-extractive fish abundance estimation with the aid of visual analysis has drawn increasing attention. Low frame rate and variable illumination in the underwater environment, however, makes conventional tracking methods unreliable. In this paper, a robust multiple fish tracking system for low-framerate underwater stereo cameras is proposed. With the result of fish segmentation, a computationally efficient block-matching method is applied to perform successful stereo matching. A multiple-feature matching cost function is utilized to give a simple but effective metric for finding the temporal match of each target. Built upon reliable stereo matching, a multipletarget tracking algorithm via the Viterbi data association is developed to overcome the poor motion continuity of targets. Experimental results show that an accurate underwater live fish tracking result with stereo cameras is achieved

GReTA - a novel Global and Recursive Tracking Algorithm in three dimensions

Tracking multiple moving targets allows quantitative measure of the dynamic behavior in systems as diverse as animal groups in biology, turbulence in fluid dynamics and crowd and traffic control. In three dimensions, tracking several targets becomes increasingly hard since optical occlusions are very likely, i.e. two featureless targets frequently overlap for several frames. Occlusions are particularly frequent in biological groups such as bird flocks, fish schools, and insect swarms, a fact that has severely limited collective animal behavior field studies in the past. This paper presents a 3D tracking method that is robust in the case of severe occlusions. To ensure robustness, we adopt a global optimization approach that works on all objects and frames at once. To achieve practicality and scalability, we employ a divide and conquer formulation, thanks to which the computational complexity of the problem is reduced by orders of magnitude. We tested our algorithm with synthetic data, with experimental data of bird flocks and insect swarms and with public benchmark datasets, and show that our system yields high quality trajectories for hundreds of moving targets with severe overlap. The results obtained on very heterogeneous data show the potential applicability of our method to the most diverse experimental situations.Comment: 13 pages, 6 figures, 3 tables. Version 3 was slightly shortened, and new comprative results on the public datasets (thermal infrared videos of flying bats) by Z. Wu and coworkers (2014) were included. in A. Attanasi et al., "GReTA - A Novel Global and Recursive Tracking Algorithm in Three Dimensions", IEEE Trans. Pattern Anal. Mach. Intell., vol.37 (2015

Three-Dimensional Neurophenotyping of Adult Zebrafish Behavior

The use of adult zebrafish (Danio rerio) in neurobehavioral research is rapidly expanding. The present large-scale study applied the newest video-tracking and data-mining technologies to further examine zebrafish anxiety-like phenotypes. Here, we generated temporal and spatial three-dimensional (3D) reconstructions of zebrafish locomotion, globally assessed behavioral profiles evoked by several anxiogenic and anxiolytic manipulations, mapped individual endpoints to 3D reconstructions, and performed cluster analysis to reconfirm behavioral correlates of high- and low-anxiety states. The application of 3D swim path reconstructions consolidates behavioral data (while increasing data density) and provides a novel way to examine and represent zebrafish behavior. It also enables rapid optimization of video tracking settings to improve quantification of automated parameters, and suggests that spatiotemporal organization of zebrafish swimming activity can be affected by various experimental manipulations in a manner predicted by their anxiolytic or anxiogenic nature. Our approach markedly enhances the power of zebrafish behavioral analyses, providing innovative framework for high-throughput 3D phenotyping of adult zebrafish behavior

How fish larvae swim: from motion to mechanics

Most of the world's 34,000 known fish species are undulatory swimmers. Their body undulations are produced by fluid-structure interaction between water and the body of the fish, powered by its muscle system. Despite these complex physics, just-hatched fish larvae can already produce effective swimming motion. How they do this is not yet fully understood. With this thesis, we aim to contribute to answering this question by examining the biomechanics of swimming of early-development larval zebrafish. With novel experimental and computational techniques, we reconstructed the dynamics of the larvae from high-speed video. These analyses highlight the challenges that larval fish face during swimming, and how the larvae have evolved to solve these challenges. In chapter 2 we reviewed the mechanics of swimming of larval fish. We examined the functional demands on the locomotory system of fish larvae: immediately after hatching, fish need to escape predators, search and hunt for food, and migrate and disperse. These demands need to be fulfilled by the larvae while undergoing large changes in their bodies, both internal and external. Furthermore, the swimming speed and size of many larvae causes them to be in the intermediate flow regime, where the nature of the flow changes considerably with changes in size or speed. In this chapter, we integrated previous literature to gain insight into how these functional demands on the locomotory system are met with the advantages and limitations of their developing bodies and the changing hydrodynamic regime. In chapter 3, we analysed near-periodic swimming of zebrafish larvae with two-dimensional inverse dynamics from motion that was manually tracked from high-speed video images. We used these data to show how the intermediate flow regime affects the swimming dynamics of fish larvae. We used the Reynolds number, which indicates the relative importance of viscous forces to inertial forces, to characterise the flow regime that the larvae swim in. Furthermore, we applied the Strouhal number, a measure of the ratio of the approximate lateral tail speed to the forward swimming speed, to express changes in swimming kinematics. We found that the Strouhal number depends inversely on the Reynolds number. Fish swimming at low Reynolds numbers tend to use relatively high Strouhal numbers, indicating that their tail-beat amplitude and frequency are high. Even the larvae swimming at the highest Reynolds numbers still use relatively high Strouhal numbers (around 0.72) compared to adult fish (typically 0.2–0.3). Swimming at intermediate Reynolds numbers is associated with high drag, requiring the larvae to use high tail-beat amplitudes and frequencies (and therefore Strouhal number) to produce sufficient thrust. This mode of swimming requires relatively high-amplitude yaw torques, resulting in large angular amplitudes and an expected high energetic cost of transport: the small size of the larvae is a burden to their swimming. Most of the previous research on fish swimming, including our chapter 3, has been done two-dimensionally. However, fish can perform complex, three-dimensional motions to escape predators, search or hunt for food, or manoeuvre through the environment. To expand our analyses to the third dimension, we developed a method to reconstruct the 3D motion of fish from multi-camera high-speed video, described in chapter 4. With an optimisation algorithm we find the 3D position, orientation, and body curvature that best fits the high-speed video frames. We demonstrated that the method allows us to reconstruct the swimming kinematics with high accuracy, while requiring minimal manual work. In addition, we developed a novel method to calculate resultant hydrodynamic forces and torques from the reconstructed motion. The described method is a valuable tool for analysing the biomechanics of swimming, providing data for future analyses of fish swimming. In chapter 5, we apply this automated tracking method to analyse fast starts of zebrafish larvae five days after fertilisation. To be able to escape predators, the main functional demands on a fast start are producing sufficient speed within a narrow time frame and being able to generate a wide range of escape directions. To investigate how these demands are met, we used a five-camera high-speed video of fast-starting zebrafish larvae with unprecedented spatiotemporal resolution. From these videos, we reconstructed the 3D motion of the larvae and the resultant hydrodynamic forces and torques. Due to their undulatory swimming style, the larvae first need to bend into a C-shape before being able to produce a propulsive tail beat. For this reason, the first stage of the start is often considered ‘preparatory’. Based on the reconstructed forces and torques, we show that the first stage of the start, in addition to its preparatory role, also serves to provide most of the reorientation of the start. After this stage, the larvae unfold their bodies, moving their tails at high speeds and thus producing large propulsive forces. The turn angle produced during a start mostly depends on the amount of body curvature in the first stage, while the escape speed mainly depends on the duration of the start. This suggests that larvae are able to independently adjust the direction and speed of their escape. Fish larvae are able to produce these escape responses and the subsequent swimming bout immediately after hatching, despite their bodies and brains still undergoing development. To understand how this is possible, we use an advanced inverse-dynamics approach, with computational fluid dynamics and a large-amplitude beam model, to reconstruct internal mechanics from the motion of the fish in chapter 6. We compute the internal bending moments from more than 100 3D-recordings of swimming over a range of developmental stages. We show that larvae use similar bending moment patterns across development, speeds and accelerations. By varying the amplitude and duration of this pattern, the larvae can adjust their swimming speed and/or acceleration. This similarity suggests that their muscle activation patterns are also similar, which would help to explain how just-hatched larvae with limited neural capacity can produce effective swimming motion across a range of speeds and accelerations. In this thesis, we demonstrated that larval fish swim in a challenging hydrodynamic regime. Despite the relatively high drag, they can produce effective swimming motions to help them survive to adulthood. We developed novel methods to quantify this motion in 3D, and from it reconstructed the external and internal mechanics. With these inverse-dynamics approaches, we show that fish larvae can likely adjust their swimming in a relatively simple way, for both fast starts and continuous swimming. Thus, complex physics do not obstruct developing larvae from swimming effectively.</p

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems