Opportunistic communication schemes for unmanned vehicles in urban search and rescue

In urban search and rescue (USAR) operations, there is a considerable amount of danger faced by rescuers. The use of mobile robots can alleviate this issue. Coordinating the search effort is made more difficult by the communication issues typically faced in these environments, such that communication is often restricted. With small numbers of robots, it is necessary to break communication links in order to explore the entire environment. The robots can be viewed as a broken ad hoc network, relying on opportunistic contact in order to share data. In order to minimise overheads when exchanging data, a novel algorithm for data exchange has been created which maintains the propagation speed of flooding while reducing overheads. Since the rescue workers outside of the structure need to know the location of any victims, the task of finding their locations is two parted: 1) to locate the victims (Search Time), and 2) to get this data outside the structure (Delay Time). Communication with the outside is assumed to be performed by a static robot designated as the Command Station. Since it is unlikely that there will be sufficient robots to provide full communications coverage of the area, robots that discover victims are faced with the difficult decision of whether they should continue searching or return with the victim data. We investigate a variety of search techniques and see how the application of biological foraging models can help to streamline the search process, while we have also implemented an opportunistic network to ensure that data are shared whenever robots come within line of sight of each other or the Command Station. We examine this trade-off between performing a search and communicating the results

Self–organised multi agent system for search and rescue operations

Autonomous multi-agent systems perform inadequately in time critical missions, while they tend to explore exhaustively each location of the field in one phase with out selecting the pertinent strategy. This research aims to solve this problem by introducing a hierarchy of exploration strategies. Agents explore an unknown search terrain with complex topology in multiple predefined stages by performing pertinent strategies depending on their previous observations. Exploration inside unknown, cluttered, and confined environments is one of the main challenges for search and rescue robots inside collapsed buildings. In this regard we introduce our novel exploration algorithm for multi–agent system, that is able to perform a fast, fair, and thorough search as well as solving the multi–agent traffic congestion. Our simulations have been performed on different test environments in which the complexity of the search field has been defined by fractal dimension of Brownian movements. The exploration stages are depicted as defined arenas of National Institute of Standard and Technology (NIST). NIST introduced three scenarios of progressive difficulty: yellow, orange, and red. The main concentration of this research is on the red arena with the least structure and most challenging parts to robot nimbleness

Learning from humans: combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task

We develop a method to learn bio-inspired foraging policies using human data. We conduct an experiment where humans are virtually immersed in an open field foraging environment and are trained to collect the highest amount of rewards. A Markov Decision Process (MDP) framework is introduced to model the human decision dynamics. Then, Imitation Learning (IL) based on maximum likelihood estimation is used to train Neural Networks (NN) that map human decisions to observed states. The results show that passive imitation substantially underperforms humans. We further refine the human-inspired policies via Reinforcement Learning (RL), using on-policy algorithms that are more suitable to learn from pre-trained networks. We show that the combination of IL and RL can match human results and that good performance strongly depends on an egocentric representation of the environment. The developed methodology can be used to efficiently learn policies for unmanned vehicles which have to solve missions in an open field environment.Comment: 24 pages, 15 figure

The Cost of Dreaming; Identifying the Underlying Social and Cultural Structures which Push/Pull Victims into Human Traffic and Commercial Sexual Exploitation in Central America

This investigation explores the international perspectives of causality of human traffic, specifically, traffic into commercial sexual exploitation. Current Western approaches to combat trafficking centre around law and order, immigration issues, and victim protection programs. While these are important for a holistic effort to deter traffic, these foci overlook prevention endeavors, thereby acting as a band-aid on a bullet wound, addressing the symptoms, but not the foundation of trafficking. Western perspectives toward prevention concentrate on economic aspects of supply and demand while crediting the root cause to be poverty. Using social exclusion theory, this thesis demonstrates that the current paradigm of viewing human trafficking in purely economic terms is an oversimplification. This project proposes to widen the focus of prevention efforts those cultural and social structures which push and pull victims into trafficking. The research is a response to an international call for further initiatives to prevent human trafficking, the recent rise of human traffic in Guatemala, Central America and the lack of research which focuses on the social links with trafficking and mainstream society. Research conducted in Guatemala, included a thirteen-month ethnography and involved one-hundred and thirteen qualitative interviews conducted in nine Guatemalan cities strategically located along trafficking routes. The target research population included women sex workers and former traffic victims from Central America and included insights from non-governmental organizations workers. Twenty-three interviewees were Central American migrants which provided insight in the wider regional structures of traffic and commercial sexual exploitation. The interviews aimed at understanding the lived experiences of exploitation in order to determine whether social exclusion affects human traffic within commercial sexual exploitation. The findings revealed the underlying social and cultural structures which reinforce human trafficking. Empirical data collected provides real-time data on trafficking networks, commercial sexual exploitation and reveals the geo-political significance of Guatemala as a hot-spot for traffic. Analysis of interviews illustrates variations in the experience of human traffic and commercial sexual exploitation which challenges current western stereotypical ideas on traffic victims. Conceptually, macro-structures—political, economic, social, and violence—are presented as a back drop for the formation of wider networks of exploitation. The exploration of violence as a push factor challenges international forced repatriation policies. Micro-structures—gender roles, family, violence, and coping strategies—are examined in the ways they perpetuate social systems of trafficking and commercial sexual exploitation. Theoretically, the thesis argues against the current paradigm which narrowly focuses on economics, but calls for the incorporation of social exclusion theory to understand the multi-dimensionality of human traffic and its wider links to society in order to open up new dialogue for prevention between the West and the majority world

A Broad View on Robot Self-Defense: Rapid Scoping Review and Cultural Comparison

With power comes responsibility: as robots become more advanced and prevalent, the role they will play in human society becomes increasingly important. Given that violence is an important problem, the question emerges if robots could defend people, even if doing so might cause harm to someone. The current study explores the broad context of how people perceive the acceptability of such robot self-defense (RSD) in terms of (1) theory, via a rapid scoping review, and (2) public opinion in two countries. As a result, we summarize and discuss: increasing usage of robots capable of wielding force by law enforcement and military, negativity toward robots, ethics and legal questions (including differences to the well-known trolley problem), control in the presence of potential failures, and practical capabilities that such robots might require. Furthermore, a survey was conducted, indicating that participants accepted the idea of RSD, with some cultural differences. We believe that, while substantial obstacles will need to be overcome to realize RSD, society stands to gain from exploring its possibilities over the longer term, toward supporting human well-being in difficult times