An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective

In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to “see” the whole robots’ workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning

Motion Planning

Motion planning is a fundamental function in robotics and numerous intelligent machines. The global concept of planning involves multiple capabilities, such as path generation, dynamic planning, optimization, tracking, and control. This book has organized different planning topics into three general perspectives that are classified by the type of robotic applications. The chapters are a selection of recent developments in a) planning and tracking methods for unmanned aerial vehicles, b) heuristically based methods for navigation planning and routes optimization, and c) control techniques developed for path planning of autonomous wheeled platforms

On systematic approaches for interpreted information transfer of inspection data from bridge models to structural analysis

In conjunction with the improved methods of monitoring damage and degradation processes, the interest in reliability assessment of reinforced concrete bridges is increasing in recent years. Automated imagebased inspections of the structural surface provide valuable data to extract quantitative information about deteriorations, such as crack patterns. However, the knowledge gain results from processing this information in a structural context, i.e. relating the damage artifacts to building components. This way, transformation to structural analysis is enabled. This approach sets two further requirements: availability of structural bridge information and a standardized storage for interoperability with subsequent analysis tools. Since the involved large datasets are only efficiently processed in an automated manner, the implementation of the complete workflow from damage and building data to structural analysis is targeted in this work. First, domain concepts are derived from the back-end tasks: structural analysis, damage modeling, and life-cycle assessment. The common interoperability format, the Industry Foundation Class (IFC), and processes in these domains are further assessed. The need for usercontrolled interpretation steps is identified and the developed prototype thus allows interaction at subsequent model stages. The latter has the advantage that interpretation steps can be individually separated into either a structural analysis or a damage information model or a combination of both. This approach to damage information processing from the perspective of structural analysis is then validated in different case studies

Planning Algorithms for Multi-Robot Active Perception

A fundamental task of robotic systems is to use on-board sensors and perception algorithms to understand high-level semantic properties of an environment. These semantic properties may include a map of the environment, the presence of objects, or the parameters of a dynamic field. Observations are highly viewpoint dependent and, thus, the performance of perception algorithms can be improved by planning the motion of the robots to obtain high-value observations. This motivates the problem of active perception, where the goal is to plan the motion of robots to improve perception performance. This fundamental problem is central to many robotics applications, including environmental monitoring, planetary exploration, and precision agriculture. The core contribution of this thesis is a suite of planning algorithms for multi-robot active perception. These algorithms are designed to improve system-level performance on many fronts: online and anytime planning, addressing uncertainty, optimising over a long time horizon, decentralised coordination, robustness to unreliable communication, predicting plans of other agents, and exploiting characteristics of perception models. We first propose the decentralised Monte Carlo tree search algorithm as a generally-applicable, decentralised algorithm for multi-robot planning. We then present a self-organising map algorithm designed to find paths that maximally observe points of interest. Finally, we consider the problem of mission monitoring, where a team of robots monitor the progress of a robotic mission. A spatiotemporal optimal stopping algorithm is proposed and a generalisation for decentralised monitoring. Experimental results are presented for a range of scenarios, such as marine operations and object recognition. Our analytical and empirical results demonstrate theoretically-interesting and practically-relevant properties that support the use of the approaches in practice

Digital Image Processing

This book presents several recent advances that are related or fall under the umbrella of 'digital image processing', with the purpose of providing an insight into the possibilities offered by digital image processing algorithms in various fields. The presented mathematical algorithms are accompanied by graphical representations and illustrative examples for an enhanced readability. The chapters are written in a manner that allows even a reader with basic experience and knowledge in the digital image processing field to properly understand the presented algorithms. Concurrently, the structure of the information in this book is such that fellow scientists will be able to use it to push the development of the presented subjects even further

Efficient multi-task allocation and path planning for unmanned surface vehicle in support of ocean operations

Presently, there is an increasing interest in the deployment of unmanned surface vehicles (USVs) to support complex ocean operations. In order to carry out these missions in a more efficient way, an intelligent hybrid multi-task allocation and path planning algorithm is required and has been proposed in this paper. In terms of the multi-task allocation, a novel algorithm based upon a self-organising map (SOM) has been designed and developed. The main contribution is that an adaptive artificial repulsive force field has been constructed and integrated into the SOM to achieve collision avoidance capability. The new algorithm is able to fast and effectively generate a sequence for executing multiple tasks in a cluttered maritime environment involving numerous obstacles. After generating an optimised task execution sequence, a path planning algorithm based upon fast marching square (FMS) is utilised to calculate the trajectories. Because of the introduction of a safety parameter, the FMS is able to adaptively adjust the dimensional influence of an obstacle and accordingly generate the paths to ensure the safety of the USV. The algorithms have been verified and evaluated through a number of computer based simulations and has been proven to work effectively in both simulated and practical maritime environments

Terrain Representation And Reasoning In Computer Generated Forces : A Survey Of Computer Generated Forces Systems And How They Represent And Reason About Terrain

Report on a survey of computer systems used to produce realistic or intelligent behavior by autonomous entities in simulation systems. In particular, it is concerned with the data structures used by computer generated forces systems to represent terrain and the algorithmic approaches used by those systems to reason about terrain

CLOUD-BASED SOLUTIONS IMPROVING TRANSPARENCY, OPENNESS AND EFFICIENCY OF OPEN GOVERNMENT DATA

A central pillar of open government programs is the disclosure of data held by public agencies using Information and Communication Technologies (ICT). This disclosure relies on the creation of open data portals (e.g. Data.gov) and has subsequently been associated with the expression Open Government Data (OGD). The overall goal of these governmental initiatives is not limited to enhance transparency of public sectors but aims to raise awareness of how released data can be put to use in order to enable the creation of new products and services by private sectors. Despite the usage of technological platforms to facilitate access to government data, open data portals continue to be organized in order to serve the goals of public agencies without opening the doors to public accountability, information transparency, public scrutiny, etc. This thesis considers the basic aspects of OGD including the definition of technical models for organizing such complex contexts, the identification of techniques for combining data from several portals and the proposal of user interfaces that focus on citizen-centred usability. In order to deal with the above issues, this thesis presents a holistic approach to OGD that aims to go beyond problems inherent their simple disclosure by providing a tentative answer to the following questions: 1) To what extent do the OGD-based applications contribute towards the creation of innovative, value-added services? 2) What technical solutions could increase the strength of this contribution? 3) Can Web 2.0 and Cloud technologies favour the development of OGD apps? 4) How should be designed a common framework for developing OGD apps that rely on multiple OGD portals and external web resources? In particular, this thesis is focused on devising computational environments that leverage the content of OGD portals (supporting the initial phase of data disclosure) for the creation of new services that add value to the original data. The thesis is organized as follows. In order to offer a general view about OGD, some important aspects about open data initiatives are presented including their state of art, the existing approaches for publishing and consuming OGD across web resources, and the factors shaping the value generated through government data portals. Then, an architectural framework is proposed that gathers OGD from multiple sites and supports the development of cloud-based apps that leverage these data according to potentially different exploitation roots ranging from traditional business to specialized supports for citizens. The proposed framework is validated by two cloud-based apps, namely ODMap (Open Data Mapping) and NESSIE (A Network-based Environment Supporting Spatial Information Exploration). In particular, ODMap supports citizens in searching and accessing OGD from several web sites. NESSIE organizes data captured from real estate agencies and public agencies (i.e. municipalities, cadastral offices and chambers of commerce) in order to provide citizens with a geographic representation of real estate offers and relevant statistics about the price trend.A central pillar of open government programs is the disclosure of data held by public agencies using Information and Communication Technologies (ICT). This disclosure relies on the creation of open data portals (e.g. Data.gov) and has subsequently been associated with the expression Open Government Data (OGD). The overall goal of these governmental initiatives is not limited to enhance transparency of public sectors but aims to raise awareness of how released data can be put to use in order to enable the creation of new products and services by private sectors. Despite the usage of technological platforms to facilitate access to government data, open data portals continue to be organized in order to serve the goals of public agencies without opening the doors to public accountability, information transparency, public scrutiny, etc. This thesis considers the basic aspects of OGD including the definition of technical models for organizing such complex contexts, the identification of techniques for combining data from several portals and the proposal of user interfaces that focus on citizen-centred usability. In order to deal with the above issues, this thesis presents a holistic approach to OGD that aims to go beyond problems inherent their simple disclosure by providing a tentative answer to the following questions: 1) To what extent do the OGD-based applications contribute towards the creation of innovative, value-added services? 2) What technical solutions could increase the strength of this contribution? 3) Can Web 2.0 and Cloud technologies favour the development of OGD apps? 4) How should be designed a common framework for developing OGD apps that rely on multiple OGD portals and external web resources? In particular, this thesis is focused on devising computational environments that leverage the content of OGD portals (supporting the initial phase of data disclosure) for the creation of new services that add value to the original data. The thesis is organized as follows. In order to offer a general view about OGD, some important aspects about open data initiatives are presented including their state of art, the existing approaches for publishing and consuming OGD across web resources, and the factors shaping the value generated through government data portals. Then, an architectural framework is proposed that gathers OGD from multiple sites and supports the development of cloud-based apps that leverage these data according to potentially different exploitation roots ranging from traditional business to specialized supports for citizens. The proposed framework is validated by two cloud-based apps, namely ODMap (Open Data Mapping) and NESSIE (A Network-based Environment Supporting Spatial Information Exploration). In particular, ODMap supports citizens in searching and accessing OGD from several web sites. NESSIE organizes data captured from real estate agencies and public agencies (i.e. municipalities, cadastral offices and chambers of commerce) in order to provide citizens with a geographic representation of real estate offers and relevant statistics about the price trend