Abstract: The ocean environment and the physical and biological processes that govern dynamics are complex. Sampling the ocean to better understand these processes is difficult given the temporal and spatial domains and sampling tools available. Biological systems are especially difficult as organisms possess behavior, operate at horizontal scales smaller than traditional shipboard sampling allows, and are often disturbed by the sampling platforms themselves. Sensors that measure biological processes have also generally not kept pace with the development of physical counterparts as their requirements are as complex as the target organisms. Here, we attempt to address this challenge by advocating the need for sensor-platform combinations to integrate and process data in real-time and develop data products that are useful in increasing sampling efficiencies. Too often, the data of interest is only garnered after post-processing after a sampling effort and the opportunity to use that information to guide sampling is lost. Here we demonstrate a new autonomous platform, where data are collected, analyzed, and data products are output in real-time to inform autonomous decision-making. This integrated capability allows for enhanced and informed sampling towards improving our understanding of the marine environment.
Abstract: Biomimetic Autonomous Underwater Vehicles (BAUVs) are Autonomous Underwater Vehicles (AUVs) that employ similar propulsion and steering principles as real fish. While the real life applicability of these vehicles has yet to be fully investigated, laboratory investigations have demonstrated that at low speeds, the propulsive mechanism of these vehicles is more efficient when compared with propeller based AUVs. Furthermore, these vehicles have also demonstrated superior manoeuvrability characteristics when compared with conventional AUVs and Underwater Glider Systems (UGSs). Further performance benefits can be achieved through coordination of multiple BAUVs swimming in formation. In this study, the coordination strategy is based on the schooling behaviour of fish, which is a decentralized approach that allows multiple AUVs to be self-organizing. Such a strategy can be effectively utilized for large spatiotemporal data collection for oceanic monitoring and surveillance purposes. A validated mathematical model of the BAUV developed at the University of Glasgow, RoboSalmon, is used to represent the agents within a school formation. The performance of the coordination algorithm is assessed through simulation where system identification techniques are employed to improve simulation run time while ensuring accuracy is maintained. The simulation results demonstrate the effectiveness of implementing coordination algorithms based on the behavioural mechanisms of fish to allow a group of BAUVs to be considered self-organizing.
Abstract: An affordable, highly articulated, child-size humanoid robot could potentially be used for various purposes, widening the design space of humanoids for further study. Several findings indicated that normal children and children with autism interact well with humanoids. This paper presents a child-sized humanoid robot (HBS-1) intended primarily for children’s education and rehabilitation. The design approach is based on the design for manufacturing (DFM) and the design for assembly (DFA) philosophies to realize the robot fully using additive manufacturing. Most parts of the robot are fabricated with acrylonitrile butadiene styrene (ABS) using rapid prototyping technology. Servomotors and shape memory alloy actuators are used as actuating mechanisms. The mechanical design, analysis and characterization of the robot are presented in both theoretical and experimental frameworks.
Abstract: The authors develop an approach to a “best” time path for Autonomous Underwater Vehicles conducting oceanographic measurements under uncertain current flows. The numerical optimization tool DIDO is used to compute hybrid minimum time and optimal survey paths for a sample of currents between ebb and flow. A simulated meta-experiment is performed where the vehicle traverses the resulting paths under different current strengths per run. The fastest elapsed time emerges from a payoff table. A multi-objective function is then used to weigh the time to complete a mission versus measurement inaccuracy due to deviation from the desired survey path.
Abstract: Control systems prototyping is usually constrained by model complexity, embedded system configurations, and interface testing. The proposed control system prototyping of a remotely-operated vehicle (ROV) with a docking hoop (DH) to recover an autonomous underwater vehicle (AUV) named AUVDH using a combination of software tools allows the prototyping process to be unified. This process provides systematic design from mechanical, hydrodynamics, dynamics modelling, control system design, and simulation to testing in water. As shown in a three-dimensional simulation of an AUVDH model using MATLAB™/Simulink™ during the launch and recovery process, the control simulation of a sliding mode controller is able to control the positions and velocities under the external wave, current, and tether forces. In the water test using the proposed Python-based GUI platform, it shows that the AUVDH is capable to perform station-keeping under the external disturbances.