Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

A Survey of User Interfaces for Robot Teleoperation

Robots are used today to accomplish many tasks in society, be it in industry, at home, or as helping tools on tragic incidents. The human-robot systems currently developed span a broad variety of applications and are typically very different from one another. The interaction techniques designed for each system are also very different, although some effort has been directed in defining common properties and strategies for guiding human-robot interaction (HRI) development. This work aims to present the state-of-the-art in teleoperation interaction techniques between robots and their users. By presenting potentially useful design models and motivating discussions on topics to which the research community has been paying little attention lately, we also suggest solutions to some of the design and operational problems being faced in this area

Using Unmanned Aerial Vehicles for Wireless Localization in Search and Rescue

This thesis presents how unmanned aerial vehicles (UAVs) can successfully assist in search and rescue (SAR) operations using wireless localization. The zone-grid to partition to capture/detect WiFi probe requests follows the concepts found in Search Theory Method. The UAV has attached a sensor, e.g., WiFi sniffer, to capture/detect the WiFi probes from victims or lost people’s smartphones. Applying the Random-Forest based machine learning algorithm, an estimation of the user\u27s location is determined with a 81.8% accuracy. UAV technology has shown limitations in the navigational performance and limited flight time. Procedures to optimize these limitations are presented. Additionally, how the UAV is maneuvered during flight is analyzed, considering different SAR flight patterns and Li-Po battery consumption rates of the UAV. Results show that controlling the UAV by remote-controll detected the most probes, but it is less power efficient compared to control it autonomously

Final Report for the DARPA/NSF Interdisciplinary Study on Human–Robot Interaction

As part of a Defense Advanced Research Projects Agency/National Science Foundation study on human–robot interaction (HRI), over sixty representatives from academia, government, and industry participated in an interdisciplinary workshop, which allowed roboticists to interact with psychologists, sociologists, cognitive scientists, communication experts and human–computer interaction specialists to discuss common interests in the field of HRI, and to establish a dialogue across the disciplines for future collaborations. We include initial work that was done in preparation for the workshop, links to keynote and other presentations, and a summary of the findings, outcomes, and recommendations that were generated by the participants. Findings of the study include— the need for more extensive interdisciplinary interaction, identification of basic taxonomies and research issues, social informatics, establishment of a small number of common application domains, and field experience for members of the HRI community. An overall conclusion of the workshop was expressed as the following— HRI is a cross-disciplinary area, which poses barriers to meaningful research, synthesis, and technology transfer. The vocabularies, experiences, methodologies, and metrics of the communities are sufficiently different that cross-disciplinary research is unlikely to happen without sustained funding and an infrastructure to establish a new HRI community

An Evaluation Schema for the Ethical Use of Autonomous Robotic Systems in Security Applications

We propose a multi-step evaluation schema designed to help procurement agencies and others to examine the ethical dimensions of autonomous systems to be applied in the security sector, including autonomous weapons systems

Improving Emergency Response and Human-Robotic Performance

Preparedness for chemical, biological, and radiological/nuclear incidents at nuclear power plants (NPPs) includes the deployment of well trained emergency response teams. While teams are expected to do well, data from other domains suggests that the timeliness and accuracy associated with incident response can be improved through collaborative human-robotic interaction. Many incident response scenarios call for multiple, complex procedure-based activities performed by personnel wearing cumbersome personal protective equipment (PPE) and operating under high levels of stress and workload. While robotic assistance is postulated to reduce workload and exposure, limitations associated with communications and the robot’s ability to act independently have served to limit reliability and reduce our potential to exploit human –robotic interaction and efficacy of response. Recent work at the Idaho National Laboratory (INL) on expanding robot capability has the potential to improve human-system response during disaster management and recovery. Specifically, increasing the range of higher level robot behaviors such as autonomous navigation and mapping, evolving new abstractions for sensor and control data, and developing metaphors for operator control have the potential to improve state-of-the-art in incident response. This paper discusses these issues and reports on experiments underway intelligence residing on the robot to enhance emergency response

Command and Control Systems for Search and Rescue Robots

The novel application of unmanned systems in the domain of humanitarian Search and Rescue (SAR) operations has created a need to develop specific multi-Robot Command and Control (RC2) systems. This societal application of robotics requires human-robot interfaces for controlling a large fleet of heterogeneous robots deployed in multiple domains of operation (ground, aerial and marine). This chapter provides an overview of the Command, Control and Intelligence (C2I) system developed within the scope of Integrated Components for Assisted Rescue and Unmanned Search operations (ICARUS). The life cycle of the system begins with a description of use cases and the deployment scenarios in collaboration with SAR teams as end-users. This is followed by an illustration of the system design and architecture, core technologies used in implementing the C2I, iterative integration phases with field deployments for evaluating and improving the system. The main subcomponents consist of a central Mission Planning and Coordination System (MPCS), field Robot Command and Control (RC2) subsystems with a portable force-feedback exoskeleton interface for robot arm tele-manipulation and field mobile devices. The distribution of these C2I subsystems with their communication links for unmanned SAR operations is described in detail. Field demonstrations of the C2I system with SAR personnel assisted by unmanned systems provide an outlook for implementing such systems into mainstream SAR operations in the future

MODELING OF INNOVATIVE LIGHTER-THAN-AIR UAV FOR LOGISTICS, SURVEILLANCE AND RESCUE OPERATIONS

An unmanned aerial vehicle (UAV) is an aircraft that can operate without the presence of pilots, either through remote control or automated systems. The first part of the dissertation provides an overview of the various types of UAVs and their design features. The second section delves into specific experiences using UAVs as part of an automated monitoring system to identify potential problems such as pipeline leaks or equipment damage by conducting airborne surveys.Lighter-than-air UAVs, such as airships, can be used for various applications, from aerial photography, including surveying terrain, monitoring an area for security purposes and gathering information about weather patterns to surveillance. The third part reveals the applications of UAVs for assisting in search and rescue operations in disaster situations and transporting natural gas. Using PowerSim software, a model of airship behaviour was created to analyze the sprint-and-drift concept and study methods of increasing the operational time of airships while having a lower environmental impact when compared to a constantly switched-on engine. The analysis provided a reliable percentage of finding the victim during patrolling operations, although it did not account for victim behaviour. The study has also shown that airships may serve as a viable alternative to pipeline transportation for natural gas. The technology has the potential to revolutionize natural gas transportation, optimizing efficiency and reducing environmental impact. Additionally, airships have a unique advantage in accessing remote and otherwise inaccessible areas, providing significant benefits in the energy sector. The employment of this technology was studied to be effective in specific scenarios, and it will be worth continuing to study it for a positive impact on society and the environment

Advancing UAV Path Planning System: A Software Pattern Language for Dynamic Environments

In the rapidly advancing domain of Unmanned Aerial Vehicle (UAV) technologies, the capability to navigate dynamic and unpredictable environments is paramount. To this end, we present a novel design pattern framework for real-time UAV path planning, derived from the established Pattern Language of Program Community (PLOP). This framework integrates a suite of software patterns, each selected for its role in enhancing UAV operational adaptability, environmental awareness, and resource management. Our proposed framework capitalizes on a blend of behavioral, structural, and creational patterns, which work in concert to refine the UAV's decision-making processes in response to changing environmental conditions. For instance, the Observer pattern is employed to maintain real-time environmental awareness, while the Strategy pattern allows for dynamic adaptability in the UAV's path planning algorithm. Theoretical analysis and conceptual evaluations form the backbone of this research, eschewing empirical experiments for a detailed exploration of the design's potential. By offering a systematic and standardized approach, this research contributes to the UAV field by providing a robust theoretical foundation for future empirical studies and practical implementations, aiming to elevate the efficiency and safety of UAV operations in dynamic environments

Automation and Control

Advances in automation and control today cover many areas of technology where human input is minimized. This book discusses numerous types and applications of automation and control. Chapters address topics such as building information modeling (BIM)–based automated code compliance checking (ACCC), control algorithms useful for military operations and video games, rescue competitions using unmanned aerial-ground robots, and stochastic control systems