Antonio Vasilijević

Underwater Vehicle Localization with Complementary Filter: Performance Analysis in the Shallow Water Environment

Rapid development of underwater technology during the last two decades yielded more affordable sensors and underwater vehicles, and, as a result, expanded their use from exclusively offshore industry towards smaller interdisciplinary research groups. Regardless of application, knowing the location of the vehicle operating underwater is crucial. Relatively inexpensive solution is sensor fusion based on a dynamic model of the vehicle aided by a Doppler Velocity Log and a Ultra-Short Base Line position system. Raw data from the sensors are highly asynchronous and susceptible to outliers, especially in shallow water environment. This paper presents detailed sensor analysis based on experimental data gathered in shallow waters, identifies outliers, presents an intuitive and simple sensor fusion algorithm and finally, discusses outlier rejection. The approach has been experimentally verified on medium size remotely operated vehicle.

Monitoring of seagrass by lightweight AUV: A Posidonia oceanica case study surrounding Murter island of Croatia

Posidonia oceanica (Neptune Grass) is an endemic species to the Mediterranean Sea. It forms dense and extensive green underwater meadows which provide important ecological functions and services and harbour highly diverse communities; as such it is identified as a priority habitat type for conservation under the EU Habitats Directive (Dir 92/43/CEE). Over the last decades many Posidonia oceanica meadows have disappeared or have been altered. Efficient monitoring is the key of the ecosystem conservation. Monitoring of vast areas covered by Posidonia oceanica is extremely difficult, costly and time consuming and generates pronounced need for new methods and tools. This case study presents potential and promote use of lightweight autonomous underwater vehicles (AUV) with the remote sensing payload as the environmentally non-destructive monitoring method. The study was performed from 2011 to 2013 on the Croatian island Murter during the ”Breaking the Surface” - international interdisciplinary field training of marine robotics and applications. Four AUVs equipped with different payloads were performing the missions in the study area. This paper presents results and analysis of different aspects important for the monitoring such as compliance with the existing monitoring indicators and descriptors used to assess the conservation status of P. oceanica, performance of the AUVs and their sensor sets, cost and time efficiency of the monitoring and geographical-localisation accuracy of the data collected.

Sigma-point Unscented Kalman Filter used for AUV navigation

This paper presents an implementation of the Sigma-point Unscented Kalman Filter (SP-UKF) used in the simulated task of open-water navigation of two types of AUV. The first simulated vehicle is a large cruise-type vehicle modeled after the Instituto Superior Tecnico, Lisbon vehicle Infante. The second is a small, almost fully actuated vehicle with tunnel thrusters modeled after the SSC Pacific, San Diego vehicle CETUS II. The SP-UKF shows itself, after properly taking care of implementation details, to be a robust methodology which allows for efficient and correct navigation, aided by several typical sensors (DVL, USBL hydroacoustic localization systems, AHRS). The influence of currents on the navigation, and the ability of estimating the current components is also researched. The navigation fix is fed back to the low-level control loops aboard each vehicles to achieve sane and rational navigation of the waterspace that follows stably and robustly the command signals.

Acoustically aided HMI for ROV navigation

Abstract Majority are ROVs underwater vehicles with relatively slow dynamics virtually providing a ROV pilot extra time to perform other tasks, such as inspections and arm operation. However, with many tasks performed simultaneously with flying the relevant information is typically dispersed on a number of screens overloading the pilots visual channel. Therefore, mishaps are likely to occur. To improve pilots’ perception of its surroundings and to unload their visual channel, a new method called AD AR (Audio Augmented Reality) which combines the concept of Augmented Reality with virtual audio-video user interface, is proposed. In this paper, the feasibility of proposed method used as an aiding tool for navigation is investigated. All experiments are performed on the state-of-the-art, realistic ROV simulator developed by Mobile & Marine Robotics Research Centre, ECE Department, University of Limerick, Ireland.

Coordinated Navigation of Surface and Underwater Marine Robotic Vehicles for Ocean Sampling and Environmental Monitoring

Water pollution generated by accidental spill of hazardous materials is a growing problem worldwide. There is an urgent need for a tool that would help environmental response teams perform rapid understanding of the location and the extent of the spill to effectively establish an appropriate response. This paper presents a cooperative robotic system for environmental monitoring consisting of an autonomous underwater vehicle (AUV) and an autonomous unmanned surface vehicle (USV). The main contributions of the paper are a systematic description of the design and implementation of the proposed cooperative robotic system, a novel human-on-the-loop (HOTL) approach applied on the system for environmental monitoring, and demonstration of the results of the open-sea experiments on pollution deliberately caused by harmless Rhodamine water tracing (WT), carried out in Cartagena, Spain, in June 2015. The proposed HOTL system provides near real-time pollution measurement data, while not consuming a significant amount of human time and effort. It supports decision-making and allows the operator to initiate the most adequate mission in a current situation, i.e., ensures mission change on-the-fly. While the AUV samples the ocean, the USV maintains the localization and communication data transfer to the control center and corrects the AUVs dead reckoning error.

CADDY - Cognitive Autonomous Diving Buddy: Two Years of Underwater Human-Robot Interaction

Divers operate in harsh and poorly monitored environments, in which the slightest unexpected disturbance, technical malfunction, or lack of attention can have catastrophic consequences. Motivated by these considerations, the “CADDY — Cognitive Autonomous Diving Buddy” FP7 project sets forth the main goal of developing a cooperative autonomous underwater robotic system to monitor and assist human divers, thus affording them increased levels of safety during the execution of challenging scientific and commercial missions. This article presents the main results obtained in the first 2 years of the project along the following main research topics: Seeing the Diver, where the focus is placed on the 3D reconstruction of a diver’s model (pose estimation and recognition of hand gestures) through remote and local sensing technologies, thus enabling behavior interpretation ; Understanding the Diver, with the objective of interpreting the model and physiological measurements of the diver in order to determine what can be called the state of the diver ; and Diver-Robot Cooperation and Control, aimed at investigating the interaction of the diver with underwater vehicles endowed with rich sensory motor skills, focusing on cooperative control and optimal formation with the diver as an integral part of the overall vehicle-diver formation.

Auditory Interface for Teleoperation - Path Following Experimental Results

Abstract For teloperated unmanned vehicles, mishaps tend to occur during the periods of high workload, in situations where the operator must perform complex and stressful tasks. However, with many tasks performed simultaneously with flying, the relevant information is typically dispersed on a number of screens overloading the operators visual channel. In order to address these unique human-factors problems associated with unmanned vehicles we suggest the use of an auditory display as a mean to reduce visual workload, to enhance situation awareness, and mitigate the visual and cognitive demands of contemporary marine teleoperations. Experiments were performed on the remotely operated surface marine platform (PlaDyPos) developed at the Laboratory for Underwater Systems and Technologies, Faculty of Electrical Engineering and Computing, University of Zagreb. The results show that the concept, guidance-by-sound is feasible in the real environment. The results are in line with previously obtained results from the real-time simulator showing that tracking quality can be further improved introducing supernormal auditory cues in order to provide better-than-normal operators auditory resolution in the frontal region. We conclude that the use of hearing in the form of the auditory display emerges as an important advantage. Since practice has a major effect on performance, there is definitely more room for improvement in using interfaces we are not trained for.

Fusing Hydroacoustic Absolute Position Fixes with AUV On-Board Dead Reckoning

Abstract This paper presents an implementation of the Sigma-point Unscented Kalman Filter (SP-UKF) used in the simulated task of open-water navigation of a large cruise-type autonomous underwater vehicle (AUV), the NPS * Aries. Open-water navigation is conducted on the basis of rate gyros, the AHRS ** , which includes accelerometers and a triaxial magnetic compass, and the DVL *** . All sensors function at many times the sampling time of the control loops, and therefore are available (with even the possibility of median or other filtering) at every sample time. Additionally, to correct for unavoidable dead reckoning drift, an inverted USBL **** system is used to sporadically fuse an absolute navigation fix with the projected solution of the dead reckoning navigation. The entire simulation environment includes a detailed dynamical model of the vehicle, non-stationary, non-Gaussian measurement noise generators, sporadic sensor failure and sliding mode controllers for heading, pitch and forward speed.

Autonomous Marine Robots Assisting Divers

Research related to diver safety, navigation and monitoring has been identified as crucial for advancing diving activities. These issues are usually dealt with by pairing up divers and adopting well defined rules for diving operations to reduce the chance of accidents. However, during more challenging dives (such as technical dives) these procedures may not be sufficient to ensure almost accident-free operations, for the divers must manoeuvre in complex 3D environments, carry cumbersome equipment, and focus attention on operational details. In this work it is stated that research and technological development in the area of cognitive robotics can significantly contribute to the effectiveness and safety of diving operations. The current research performed in LABUST is based on an autonomous surface platform for following divers and transmitting GPS signal to the underwater. Future envisioned applications include the development of a cognitive autonomous diving buddy consisting of both the surface platform and an underwater vehicle that will serve as diving ”guide”, ”slave” and ”observer”.

Texture segmentation applied to P. Oceanica Beds' upper boundary tracking by ROVs

Abstract The paper deals with an image processing technique for texture segmentation. By way of texture segmentation, a binary image is constructed and used to fit a line of the dominant direction of propagation of the texture in the image plane. The texture is captured by an oblique angle that positions the image plane in a near vertical orientation to the sea bottom plane. The texture being recognized in the experiment is that of Posidonion Oceanicœ , the benthic community (meadow or bed) of the Neptune grass Mediterranean endemic. It is the motivation of this paper for the dominant direction of propagation of the texture segment in the image plane to be used as a measure of the true direction of propagation of the upper border of Posidonion Oceanicœ in a feedback control loop that will enable the vehicle to autonomize the task of upper border tracking. The algorithm for extraction features four distinct phases: multi-resolution analysis using wavelets, vector quantization, post-processing of the obtained binary image and the extraction of the line parameters. The classification and line-fitting procedure are computationally optimized and made more robust by using weights in the Least Squares fitting procedure, and using nonlinear binary-image domain processing.