Despite the fact that a large number of research studies have been conducted in the field of search and rescue robotics, significantly little attention has been given to the development of rescue robots capable of performing physical rescue interventions, including loading and transporting victims to a safe zone—i.e., casualty extraction tasks. The aim of this study is to develop a mobile rescue robot that could assist first responders when saving casualties from a dangerous area by performing a casualty extraction procedure whilst ensuring that no additional injury is caused by the operation and no additional lives are put at risk. In this paper, we present a novel design of ResQbot 2.0—a mobile rescue robot designed for performing the casualty extraction task. This robot is a stretcher-type casualty extraction robot, which is a significantly improved version of the initial proof-of-concept prototype, ResQbot (retrospectively referred to as ResQbot 1.0), that has been developed in our previous work. The proposed designs and development of the mechanical system of ResQbot 2.0, as well as the method for safely loading a full-body casualty onto the robot’s ‘stretcher bed’, are described in detail based on the conducted literature review, evaluation of our previous work, and feedback provided by medical professionals. We perform simulation experiments in the Gazebo physics engine simulator to verify the proposed design and the casualty extraction procedure. The simulation results demonstrate the capability of ResQbot 2.0 to carry out safe casualty extractions successfully.
In recent years, there has been a growing concern worldwide about climate change and the corresponding apparent increase in the risk and frequency of flooding and about the implications for a wide range of river basin management issues. This paper describes the United Kingdom government's approach to implementing Catchment Flood Management Plans (CFMPs), which will provide a largescale strategic planning framework for the integrated management of flood risk to people and the development of the natural environment in a sustainable manner. This unified approach is to be adopted across England and Wales, with a view to establishing a unified framework to study flood management in each major catchment. Following on from this introduction to the U.K. approach to high-level flood management, details are given of a study where better water quality management during flood flow conditions has been shown to require a catchment-wide approach to reducing diffuse source pollution from agricultural regions. This study also shows that without this holistic approach to water management, a major cause of non-compliance with an EU Directive would not have been established for this river basin.
The efficient allocation of increasingly scarce water resources is a growing challenge worldwide, particularly during times of drought. This paper describes the development and application of an innovative technique to optimize the allocation of raw water supply to the city of London, UK during a period of drought in 2006. Using genetic algorithms, an optimization tool was developed to derive near-optimal operating strategies for the water company's multiple reservoir system for different projected rainfall scenarios and also to test the robustness of drought contingency strategies for operating the reservoirs down to a lower level under a severe drought condition. The project demonstrated that this approach is rigorous yet practical, the optimization technique is robust and effective and that optimal water allocation is an efficient measure to overcome water scarcity under drought conditions and mitigate consequent impacts. The potential application of genetic algorithms to the day to day operation of a complex water resource system represents a step-change in the industry's approach to managing such systems.
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