Master's Thesis from the year 2016 in the subject Engineering - Robotics, Mansoura University, language: English, abstract: This thesis studies strategies for humanitarian demining using robotic units. The author presents a low-cost system for landmines detection. The proposed system uses fusion of low cost multi sensors instead of using very expensive one. The proposed robot used sensor fusion technique to increase the probability of mine detection. The author has developed decision level fusion to decrease false alarm of mines detection. He used complete coverage path planning to find all possible mines in the environment. The author proposed using multiple robots with the same structure to use complete coverage path in parallel way to save the time. He proposed effective obstacle avoidance algorithm to help the robot moves in autonomous motion. The proposed robot is light in order not to trigger mines and be destroyed. He proposed effective method to destroy mines where they are using arm on the robot to help defusing method. The purpose of the thesis is to give an efficient solution for the landmines problem. By using robots that are capable of exploring and destroying buried landmines. The author also aimed to make the proposed robot with simle components to provide the soldiers and local landmines environments citizens with effective solution that they can use to save their lives.

The objective of this thesis is to develop detection algorithm to can solve socially challenging issue of Landmine mapping & removal. Landmines which used to be a safety measure during wars, play a dangerous role in civilian life, in and around the post combat regions with approximately 78 countries observing an estimate of 42 human lives killed every day. To prevent the number of casualties and manual mine clearance, mobile robots can be used for detection & mapping of the mine field region. Mapping, detection and avoidance are the primary challenges faced on a landmine removal. In this thesis, mine center is estimated using non-linear optimization and validated through simulations for mapping. Distinguishing between the surrogate mines from the metals is accomplished using Support Vector Machine (SVM) classification, an algorithm which is formulated and validated through simulations. After detection and mapping of mines, a potential field method is employed for avoidance in simulation and incorporated the ROS (Robot Operating System) Navigation Stack on the actual robot which follows selective A* and Dijkstra's algorithm. Results show that the Gaussian field parameter estimation localizes the mine appropriately even if the detected signals are not on the center of the mine and this is achieved through constrained non-linear optimization. This adds a repulsive force around the mine avoiding the step-over with a new navigation path generation. The SVM classifier simulations provide a clear distinguishing base line between the mines and metals based on the three channel data inputted. In future, with further anomalies into consideration, a working autonomous robot would be achieved with detection, mapping and avoidance of landmines.

There have been major recent advances in robotic systems that can replace humans in undertaking hazardous activities in demanding or dangerous environments. Published in association with the CLAWAR (Climbing and Walking Robots and Associated Technologies Association) (www.clawar.org), this important book reviews the development of robotic systems for de-mining and other risky activities such as fire-fighting.Part one provides an overview of the use of robots for humanitarian de-mining work. Part two discusses the development of sensors for mine detection whilst Part thee reviews developments in both teleoperated and autonomous robots. Building on the latter, Part four concentrates on robot autonomous navigation. The final part of the book reviews research on multi-agent-systems (MAS) and the multi-robotics-systems (MRS), promising tools that take into account modular design of mobile robots and the use of several robots in multi-task missions.With its distinguished editors and international team of contributors, Using robots in hazardous environments: landmine detection, de-mining and other applications is a standard reference for all those researching the use of robots in hazardous environments as well as government and other agencies wishing to use robots for dangerous tasks such as landmine detection and disposal. Reviews the development of robotic systems for de-mining and other risky activities Discusses the development and applications of sensors for mine detection using different robotic systems Examines research on multi-agent-systems and multi-robotics systems

Anti-personnel Landmine Detection for Humanitarian Demining reports on state-of-the-art technologies developed during a Japanese National Research Project (2002–2007). The conventional method of landmine detection is using metal detectors to sense the metal in mines, but often other metal fragments in minefields camouflage landmines and hinder progress using this form of demining. The challenge is to develop detection systems that can discriminate between AP landmines and random metal fragments. The JST adopted research proposals and the results are reported here. This book concentrates on aspects of three approaches to AP mine detection: enhancing and confirming the results of metal-detection scans using GPR; using robot vehicles and manipulators to operate within minefields remotely; and methods of sensing the explosives within mines. Results are presented in the fields of GPR, nuclear quadrupole resonance, neutron thermal analysis and biosensors. The integration of these methods for workable robot operation is demonstrated. The project was carried out in conjunction with mine action centers in Croatia, Cambodia and Afghanistan. Evaluation data from field trials are also given.

Insects are extremely successful creatures, thriving in our ever-changing and unpredictable world. One of the factors behind their success is the use of odour to increase their efficiency when searching for food, to help navigate between a source of food and their nest and to enable them to find a mate. Mobile robots would have their capabilities greatly enhanced if they could make use of similar techniques. This important book describes current research aimed at giving robots the ability to generate, detect and discriminate between odours, together with the control algorithms using such sensory information.

This book provides state-of-the-art scientific and engineering research findings and developments in the area of mobile robotics and associated support technologies. It contains peer-reviewed articles presented at the CLAWAR 2008 conference. Robots are no longer confined to industrial manufacturing environments; rather, a great deal of interest is invested in the use of robots outside the factory environment. The CLAWAR conference series, established as a high-profile international event, acts as a platform for dissemination of research and development findings to address the current interest in mobile robotics in meeting the needs of mankind in various sectors of the society. These include personal care, public health, and services in the domestic, public and industrial environments. The editors of the book have extensive research experience and publications in the area of robotics in general, and in mobile robotics specifically.