A Sensor Ontology For The Domain Of Firefighting Robots

Fires create thousands of dollars in damage and thousands of deaths each year. Firefighters risk their lives everyday and are often killed in action. Firefighting robots may be able to reduce the loss of lives and damage due to fires. Robots are often used for redundant tasks that require the consistency and efficiency of a machine. They are especially optimal for tasks that require strength that exceeds that of a typical human being or for environments that are hazardous to people. Robots\u27 metallic exteriors are far more durable and easier to replace than flesh and blood, thus they are ideal for fighting fire that may be unreachable or too dangerous for humaning beings. Firefighting robots are most often shaped like tanks and are equipped with fire extinguishers, sensors, and cameras. The robots are typically operated via remote control and lack autonomy. Because of the volatile nature of fires, it is difficult for software engineers to create algorithms to make firefighting robots more autonomous. Ontologies are commonly used for sharing domain information and structuring and analyzing data. This study proposes using an ontology that is designed specifically for a firefighting robot programmed to rescue a human in danger in order to make a decision making algorithm. The methodology uses ontological tools to build the ontology. A decision-making algorithm is created using the information that is stored in the ontology. The study is evaluated on the accuracy rate of making the correct decision. It is also evaluated on if the decision-making algorithm performs significantly better than decisions chosen at random

A review and comparison of ontology-based approaches to robot autonomy

Within the next decades, robots will need to be able to execute a large variety of tasks autonomously in a large variety of environments. To relax the resulting programming effort, a knowledge-enabled approach to robot programming can be adopted to organize information in re-usable knowledge pieces. However, for the ease of reuse, there needs to be an agreement on the meaning of terms. A common approach is to represent these terms using ontology languages that conceptualize the respective domain. In this work, we will review projects that use ontologies to support robot autonomy. We will systematically search for projects that fulfill a set of inclusion criteria and compare them with each other with respect to the scope of their ontology, what types of cognitive capabilities are supported by the use of ontologies, and which is their application domain.Peer ReviewedPostprint (author's final draft

An Ontological Approach to Autonomous Navigational Decision Making in Aircraft Systems

Aircraft systems are becoming increasingly complex, and automation increasingly necessary for safe aircraft operation. Current industry trends are encouraging either a reduction of crew num- bers or complete elimination. After surveying the evolution of aircraft automation systems, pilot tasks and situational awareness, we argue that a hurdle to crew reduction is that of autonomous navigation. In this thesis, we put forth an ontology based approach for defining autonomous navigational decision making. The ontology is designed to capture elements representing the environment in which aircraft operate; the “air environment”. An expert system is then pro- grammed and uses the ontology as its knowledge base. Combining the environmental ontology with a second one describing a generic air vehicle, the expert system is programmed to make navigational decisions based on environment, vehicle state and mission. Case studies show the functionality of the implementation, and a validation study demonstrates the feasibility of the solution. The thesis closes by relating it to other research and recently released industry avionics solutions

Hybrid Cloud Model Checking Using the Interaction Layer of HARMS for Ambient Intelligent Systems

Soon, humans will be co-living and taking advantage of the help of multi-agent systems in a broader way than the present. Such systems will involve machines or devices of any variety, including robots. These kind of solutions will adapt to the special needs of each individual. However, to the concern of this research effort, systems like the ones mentioned above might encounter situations that will not be seen before execution time. It is understood that there are two possible outcomes that could materialize; either keep working without corrective measures, which could lead to an entirely different end or completely stop working. Both results should be avoided, specially in cases where the end user will depend on a high level guidance provided by the system, such as in ambient intelligence applications. This dissertation worked towards two specific goals. First, to assure that the system will always work, independently of which of the agents performs the different tasks needed to accomplish a bigger objective. Second, to provide initial steps towards autonomous survivable systems which can change their future actions in order to achieve the original final goals. Therefore, the use of the third layer of the HARMS model was proposed to insure the indistinguishability of the actors accomplishing each task and sub-task without regard of the intrinsic complexity of the activity. Additionally, a framework was proposed using model checking methodology during run-time for providing possible solutions to issues encountered in execution time, as a part of the survivability feature of the systems final goals

Control of robot swarms through natural language dialogue: A case study on monitoring fires

There are numerous environmental and non-environmental disasters happening throughout the world, representing a big danger to common people, community helpers, to the fauna and flora. Developing a program capable of controlling swarms of robots, using natural language processing (NLP) and further on, a speech to text system, will enable a more mobile solution, with no need for keyboard and mouse or a mobile device for operating with the robots. Using a welldeveloped NLP system will allow the program to understand natural languagebased interactions, making this system able to be used in different contexts. In firefighting, the use of robots, more specifically drones, enables new ways to obtain reliable information that before was based on guesses or knowledge from someone who had long-time experience on field. Using a swarm of robots to monitor fire enables innumerous advantages, from the creation of a dynamic fire map, climate information inside the fire, to finding lost firefighters on field through the generated map. This work uses firefighting as a case-study, but other situations can be considered, like searching someone in the sea or searching for toxins in an open environmental area.Existem muitos desastres ambientais e não ambientais em todo o mundo, representando um grande perigo para pessoas comuns, ajudantes da comunidade e para a fauna e flora. O desenvolvimento de um programa capaz de controlar enxames de robôs, usando Processamento Computacional da Língua (PCL) e, posteriormente, um sistema de fala-para-texto, permitirá uma solução mais móvel, sem necessidade de teclado e rato ou dispositivos móveis para operar com os robôs. O uso de um sistema bem desenvolvido de PCL permitirá que o programa entenda interações baseadas em linguagem natural, tornando-o capaz de ser usado em diferentes contextos. O uso de robôs (mais especificamente drones) no combate a incêndios, permite novas maneiras de obter informações confiáveis que antes eram baseadas em suposições ou conhecimentos de pessoas com longa experiência em campo. O uso de um enxame de robôs para monitorizar o incêndio permite inúmeras vantagens, desde a criação de um mapa dinâmico do incêndio, informações climáticas dentro do mesmo, até encontrar bombeiros perdidos no campo, através do mapa gerado pelos robôs. Este trabalho usa o combate a incêndios como um estudo de caso, mas outras situações podem ser consideradas, como procurar alguém no mar ou procurar toxinas numa área ambiental aberta

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

COIN@AAMAS2015

COIN@AAMAS2015 is the nineteenth edition of the series and the fourteen papers included in these proceedings demonstrate the vitality of the community and will provide the grounds for a solid workshop program and what we expect will be a most enjoyable and enriching debate.Peer reviewe