https://users.encs.concordia.ca/~ymzhang/publications/ARC32-2-98Zhang_pp.229-252.pdf

Bibliographical review on reconfigurable fault-tolerant control systems

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

Unmanned surface vehicles: An overview of developments and challenges

Kalman filters have received much attention with the increasing demands for robotic automation. This paper briefly surveys the recent developments for robot vision. Among many factors that affect the performance of a robotic system, Kalman filters have made great contributions to vision perception. Kalman filters solve uncertainties in robot localization, navigation, following, tracking, motion control, estimation and prediction, visual servoing and manipulation, and structure reconstruction from a sequence of images. In the 50th anniversary, we have noticed that more than 20 kinds of Kalman filters have been developed so far. These include extended Kalman filters and unscented Kalman filters. In the last 30 years, about 800 publications have reported the capability of these filters in solving robot vision problems. Such problems encompass a rather wide application area, such as object modeling, robot control, target tracking, surveillance, search, recognition, and assembly, as well as robotic manipulation, localization, mapping, navigation, and exploration. These reports are summarized in this review to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed in an abstract level.

Kalman Filter for Robot Vision: A Survey

A survey of dynamic positioning control systems

The high-risk nature of SCUBA diving activities is 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. Technological advancement and research related to diver safety, navigation and monitoring has been identified as crucial for advancing diving activities. This paper reports current state of research performed at UNIZG-FER related to an autonomous overactuated surface platform used for following divers and transmitting GPS signal to the underwater. The implemented guidance and control algorithms are described and simulations obtained on realistic models developed in the ROS environment are provided. Special attention is given to algorithms for diver tracking by using measurements from a USBL. Diver motion estimators are used to improve the performance of the sparse and noisy USBL measurements. The results presented in this paper are a starting point for in-the-field experiments expected to take place in the real-world environment.

Guidance and control of an overactuated autonomous surface platform for diver tracking

Autonomous underwater navigation presents a whole set of challenges to be resolved in order to become adequately accurate and reliable. That is particularly critical when human divers work in close collaboration with autonomous underwater vehicles (AUVs). In absence of global positioning signals underwater, acoustic based sensors such as LBL (long-baseline), SBL (short-baseline) and USBL (ultrashort-baseline) are commonly used for navigation and localization. In addition to these low-bandwidth and high latency technologies, cameras and sonars can provide position measurements relative to the vehicle which can be used as an aid for navigation as well as for keeping a safe working distance between the diver and the AUV. While optical cameras are highly affected by water turbidity and lighting conditions, sonar images often become hard to interpret using conventional image processing methods due to image granulation and high noise levels.This paper focuses on finding a robust and reliable sonar image processing method for detection and tracking of human divers using convolutional neural networks. Machine learning algorithms are making a huge impact in computer vision applications but are not always considered when it comes to sonar image processing. After presenting commonly used image processing techniques the paper will focus on giving an overview of state-of-the-art machine learning algorithms and explore their performance in custom sonar image dataset processing. Finally, the performance of these algorithms will be compared on a set of sonar recordings to determine their reliability and applicability in a real-time operation.

Convolutional Neural Network Architectures for Sonar-Based Diver Detection and Tracking

Udžbenik se bavi analizom linearnih sustava automatskog upravljanja. Pokrivene su teme: stabilnost, osjetljivost, robusnost, matematicki modeli, diskretni sustavi upravljanja, tipicni regulatori, stohasticki sustavi.

Automatic Control : Analysis of linear systems

Given the fact that AUV dynamics change depending on the payload, finding a mathematical model in a rather small period of time is quite important. Classical openloop identification methods give accurate parameter identification, but are also time consuming. In the paper we present an identification method based on induced self-oscillations, which has proved to be applicable to underwater vehicles. In addition to that, an error analysis for the proposed method is presented. Experimental results obtained on an underwater vehicle are given and compared to the results obtained using open-loop identification algorithms.

/pdf/auv-identification-by-use-of-self-oscillations-2eci19gleu.pdf

Auv identification by use of self-oscillations

Guidance through waypoints is common for small autonomous marine vehicles Guidance by the line of sight, the basic waypoint guidance algorithm, is very simple, computationally inexpensive, and flexible to sudden changes in the desired path specification On the other side, the basic algorithm achieves unoptimal vehicle trajectory, ignores possible side disturbances as sea currents, and can even lead to deadlock situations Therefore it should be improved to use in the real world applications This paper introduces several such improvements: missed waypoint detection to prevent deadlocks, novel reference heading correction method to give smoother vehicle path in turns at waypoints, and sea current compensation method to cancel its influence This improvements address the mentioned flaws of the basic algorithm, as is demonstrated by the simulations, and yet keep it simpler than is the case for the most used waypoint-derived guidance methods

Zoran Vukić

Papers

Guidance and control of an overactuated autonomous surface platform for diver tracking

Convolutional Neural Network Architectures for Sonar-Based Diver Detection and Tracking

Automatic Control : Analysis of linear systems

Auv identification by use of self-oscillations

Improved basic planar algorithm of vehicle guidance through waypoints by the line of sight