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.
Table of Contents
Chapter 1: Introduction
1.1 Landmines over the world
1.2 Challenges
1.3 Motivations
1.4 Contributions
1.5 Thesis Outline
Chapter 2: Landmines detection strategies
2.1 Landmines Detection Overview
2.1.1 Classification of Mines
2.2 Mine Detection Technologies
2.3 Metal Detector
2.4 Electromagnetic Methods
2.4.1 Ground Penetrating Radar (GPR)
2.4.2 Nuclear Quadruple Resonance (NQR)
2.4.3 Microwaves
2.4.4 Electrical Impedance Tomography(EIT)
2.4.5 Infrared Method
2.4.6 X-Ray Backscatter Method
2.4.7 Sound and Ultrasound
2.4.8 Neutron Method
2.5 Acoustic/Seismic
2.6 Biological Method
2.6.1 Dogs and Rats
2.6.2 Bees
2.6.3 Bacteria
2.6.4 Antibodies method
2.6.5 Chemical Methods
2.7 Mechanical Methods
2.7.1 Probes and Prodders
2.7.2 Mine Clearing Machines
2.8 State of discussed solutions
2.9 Robot detecting strategies
2.9.1 Disadvantages of Robots
2.10 Summary
Chapter 3: Demining robot techniques
3.1 Motion planning
3.1.1 Motion planning Problem
3.1.2 Locomotion
3.1.3 Motion system
3.1.4 Motion Planning Techniques
3.1.4.1 Sampling-Based Planning
3.1.4.2 Probabilistic Roadmap Method
3.1.4.3 Graph Search
3.1.4.4 Uninformed Search
3.1.4.5 Heuristic Search
3.1.4.6 A* Algorithm
3.1.4.7 Complete coverage Technique
3.1.5 Area Mapping
3.2 Sensor Fusion
3.2.1 Sensor fusion Applications
3.2.2 The multiple sensors integration
3.2.3 Multiple Sensors Fusion Advantages
3.2.4 Sensor fusion problems
3.2.5 Multisensor Fusion
3.2.5.1 The Integration Functions
3.2.5.2 The Rule-Based and Network System
3.2.6 Multisensor Fusion Levels
3.2.6.1 Signal-Level Fusion
3.2.6.2 Pixel Level Fusion
3.2.6.3 Feature-Level Fusion
3.2.6.4 Decision Level Fusion
3.2.7 Sensor fusion system in landmines detection
Chapter 4: Related Work
4.1 Landmines Detection by Robots
4.2 Summary
Chapter 5: The proposed framework
5.1 The Proposed Low-Cost Robot System
5.2 Motion Planning
5.3 Low cost robot structure
5.4 Multi-sensor Fusion (Decision Level Fusion)
5.5 The vision system
5.6 Destroying mines
5.7 Conclusion
Chapter 6: The Experimental Results
6.1 System Components
6.1.1 Chemical sensor
6.1.2 Metal Detector
6.1.3 Ultrasound Sensor
6.1.4 Camera Sensor
6.2 Experimental Results
6.3 Discussion
6.4 Conclusion
Chapter 7: Conclusions
7.1 Conclusions
7.2 Future Work
Research Objectives and Thematic Focus
This thesis aims to develop an efficient, low-cost autonomous robotic system for the detection and demining of buried landmines. The primary research question centers on how to integrate multi-sensor fusion and effective motion planning to improve detection accuracy, reduce false alarms, and mitigate risks to human operators compared to existing, expensive demining technologies.
- Design of a cost-effective autonomous mobile robot for landmine exploration.
- Implementation of complete coverage path planning algorithms for systematic minefield searching.
- Development of multi-sensor data fusion (decision-level) to minimize false detection rates.
- Integration of robotic arms and obstacle avoidance algorithms for safe autonomous navigation and mine disposal.
Excerpt from the Book
3.1.4.1 Sampling-Based Planning
Sampling-based algorithms cannot avoid obstacles directly but by the collision detection and the structure of constructed data. Latombe et al. [20] presented the Randomized Path Planner that was the first understood inspecting based movement planner. It found a solution for issues with numerous level of degree of freedom; it supported randomization as a method for discovering arrangements in the high-dimensional design space. The main problem with this algorithm that it is difficult to estimate the overall cost as it uses randomization.
In the beginning, the planner moves in the field until a local minimum is reached. When the minimum is the global minimum, the goal has been reached. Else, it continues in random walks to escape from the local minimum. Then, the planner slides the field until the goal state has been reached or the defined time finished. The main problem with this algorithm that The planner cannot know that a problem has no solution, and so it will never end. The way to better execution is that to build great potential fields. At the point when the fields result in numerous nearby minima, the organizer can perform ineffectively.
Summary of Chapters
Chapter 1: Introduction: Provides an overview of the global landmine problem, its impact on civilians, and the specific challenges and motivations behind developing a low-cost robotic solution.
Chapter 2: Landmines detection strategies: Reviews existing manual, mechanical, and robotic demining techniques, evaluating their strengths, limitations, and the necessity for improved autonomous methods.
Chapter 3: Demining robot techniques: Discusses critical robot technologies, focusing on motion planning algorithms and sensor fusion concepts essential for high-accuracy mine detection.
Chapter 4: Related Work: Analyzes previously published research on robotic landmine detection systems, highlighting successful models and identified gaps in current technologies.
Chapter 5: The proposed framework: Details the design and architecture of the proposed low-cost robotic system, including sensor integration and the complete coverage path planning approach.
Chapter 6: The Experimental Results: Presents the findings from simulations and field tests, demonstrating the efficacy of the proposed system in terms of detection accuracy and reliability.
Chapter 7: Conclusions: Summarizes the research findings, confirms the success of the prototype, and provides recommendations for future improvements such as nanotechnology applications.
Keywords
Landmines, Demining, Autonomous Mobile Robots, Sensor Fusion, Motion Planning, Complete Coverage Algorithm, Decision Level Fusion, Obstacle Avoidance, Low-Cost System, Mine Detection, Robotics, Artificial Intelligence, Embedded Systems, Signal Processing, Humanitarian Demining.
Frequently Asked Questions
What is the core focus of this research?
The work focuses on creating a cost-effective autonomous mobile robot capable of detecting and defusing buried landmines to protect human deminers.
What are the primary thematic areas explored?
The study explores robot locomotion, path planning, multi-sensor data integration (sensor fusion), and strategies for autonomous obstacle avoidance in minefields.
What is the main research objective?
The objective is to minimize the human risk and financial cost associated with demining by using a low-cost, multi-sensor robotic system that achieves high accuracy.
Which scientific methods are utilized?
The author employs complete coverage path planning algorithms, decision-level sensor fusion (using metal detectors, chemical sensors, cameras, and ultrasound), and experimental testing in simulated minefield environments.
What is covered in the main body of the work?
The main body covers the theoretical background of detection strategies, the motion planning techniques, the technical design of the proposed robotic framework, and the empirical results of the performance evaluation.
What are the characterizing keywords of the thesis?
Key terms include landmines, demining, sensor fusion, autonomous robots, complete coverage, and low-cost detection systems.
How does decision-level fusion improve the system?
Decision-level fusion integrates independent inputs from multiple sensors to confirm a detection; if multiple sensors report a mine, the probability of mine existence is confirmed, effectively reducing false alarms.
Why is the "Complete Coverage" algorithm important for this robot?
This algorithm ensures that the robot systematically scans every point in the field at least once, which is critical for ensuring no mines are overlooked in unknown or high-risk areas.
- Quote paper
- Ahmed Ismail (Author), 2016, Landmines Detection by Using Mobile Robots, Munich, GRIN Verlag, https://www.grin.com/document/373194
