GIS-based Mission Support System for Wilderness Search and Rescue with Heterogeneous Agents (original) (raw)
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Proceedings of the AAAI Conference on Artificial Intelligence
Current practice in Wilderness Search and Rescue (WiSAR) is analogous to an intelligent system designed to gather and analyze information to find missing persons in remote areas. The system consists of multiple parts - various tools for information management (maps, GPS, etc) distributed across personnel with different skills and responsibilities. Introducing a camera-equipped mini-UAV into this task requires autonomy and information technology that itself is an integrated intelligent system to be used by a sub-team that must be integrated into the overall intelligent system. In this paper, we identify key elements of the integration challenges along two dimensions: (a) attributes of intelligent system and (b) scale, meaning individual or group. We then present component technology that offload or supplement many responsibilities to autonomous systems, and finally describe how autonomy and information are integrated into user interfaces to better support distributed search across ti...
A demonstration of a simulation tool for planning robust military village searches
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In the current military environment, village searches are conducted daily by a variety of search team types. Staff officers planning these resource allocation problems currently rely on experience and simple data tables to develop the plans. The Robust People, Animals, and Robots Search (RoPARS) planning tool for village searches developed at Colorado State University can assist military planners with this tedious process. The tool consists of a graphical user interface and a resource allocation engine. Its output is a mission plan that is robust against uncertainty in the battlefield environment (e.g., unit speed, temperature, enemy contact). The contributions of this paper include the RoPARS tool and its robustness concepts, mathematical models, and resource allocation heuristics.
A Graphical User Interface for Simulating Robust Military Village Searches
-In the current military environment, village searches are conducted daily. To accomplish a village search task in accordance with orders provided by higher headquarters, the mission leaders must plan and allocate resources (e.g., soldiers, robots, military working dogs, unmanned aerial vehicles) efficiently. The plans these leaders create are based on personal experience and planning data found in military field manuals. The Robust People, Animals, and Robots Search (RoPARS) planning tool for village search developed at Colorado State University can assist military leaders in the planning process. The tool consists of a graphical user interface and a resource allocation engine. This tool allows a user to create a simulation for a given village. These simulations allow military leaders to visualize how a given plan would be executed and to develop plans for the mission that are robust against uncertainty in the environment.
Search and Rescue Optimal Planning System
2010 13th International Conference on Information Fusion, 2010
In 1974 the U.S. Coast Guard put into operation its first computerized search and rescue planning system CASP (Computer-Assisted Search Planning) which used a Bayesian approach implemented by a particle filter to produce probability distributions for the location of the search object. These distributions were used for planning search effort. In 2003, the Coast Guard started development of a new decision support system for managing search efforts called Search and Rescue Optimal Planning System (SAROPS). SAROPS has been operational since January, 2007 and is currently the only search planning tool that the Coast Guard uses for maritime searches. SAROPS represents a major advance in search planning technology. This paper reviews the technology behind the tool.
Successful Search and Rescue in Simulated Disaster Areas
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RoboCupRescue Simulation is a large-scale multi-agent simulation of urban disasters where, in order to save lives and minimize damage, rescue teams must effectively cooperate despite sensing and communication limitations. This paper presents the comprehensive search and rescue approach of the ResQ Freiburg team, the winner in the RoboCupRescue Simulation league at RoboCup 2004. Specific contributions include the predictions of travel costs and civilian life-time, the efficient coordination of an active disaster space exploration, as well as an any-time rescue sequence optimization based on a genetic algorithm. We compare the performances of our team and others in terms of their capability of extinguishing fires, freeing roads from debris, disaster space exploration, and civilian rescue. The evaluation is carried out with information extracted from simulation log files gathered during RoboCup 2004. Our results clearly explain the success of our team, and also confirm the scientific approaches proposed in this paper.
GIS-BASED SEARCH THEORY APPLICATION FOR SEARCH AND RESCUE PLANNING
2007
iii I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. Name, Last name: Emrah, Söylemez Signature: iv ABSTRACT GIS-BASED SEARCH THEORY APPLICATION FOR SEARCH AND RESCUE PLANNING SÖYLEMEZ, Emrah
Agent Systems for Coalition Search and Rescue Task Support
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The Coalition Search and Rescue Task Support project shows cooperative agents supporting a highly dynamic mission in which AI task planning, inter-agent collaboration, workflow enactment, policy-managed services, semantic web queries, semantic web services matchmaking and knowledge-based notifications are employed.
Utulity of Gis in Search and Rescue Operations (Case Study: Kütahya-Tavşanli)
The main purpose of search and rescue operations is making effective and efficient searches with the ultimate goal of saving lives in the determined area. Two key factors are important in these operations. The first is to determine and specify the incident area by shrinking it; since determining a smaller search area decreases the search time. Secondly, reaching this area in an optimal way, so that the search team will not loose time during the operations. Use of Geographic Information Systems (GIS) assists search and rescue teams in favour of these two key factors. By using GIS techniques; firstly, probability maps, which show most probable locations containing the target, can be generated. Secondly, optimal routes to the search and rescue teams can be suggested. The case study is about a plane crash near Kütahya, Turkey which occurred in 2003.
Robotics and Automation (ICRA), …, 2011
Exploration strategies play an important role in influencing the performance of an autonomous mobile robot exploring and mapping an unknown environment. Although several exploration strategies have been proposed in the last years, their experimental evaluation and comparison are still largely unaddressed. In this paper, we quantitatively evaluate exploration strategies by experimentally comparing, in a simulation setting, a representative sample of techniques taken from literature. From a broader perspective, our work also contributes to the development of good experimental methodologies in the field of autonomous mobile robotics by promoting the principles of comparison, reproducibility, and repeatability of experiments.