landmines detection by robots presentation

Mansoura UniversityFaculty of Computers and Information

Information Systems Department

By

Ahmed IsmailB.SC. Of Information Systems

Faculty of computers and InformationMansoura University

Landmines Detection By Using Mobile Robots

باستخدام " اآلرضية اآللغام عن الكشفاآللى "االنسان

Assoc. Prof. Hazem ElBakryDepartment of Information Systems,

Faculty of Computers and Information Mansoura University

Assoc. Prof. Mohamed ElmogyDepartment of Information Technology, Faculty of Computers and Information,

Mansoura University

Under Supervision of

Outline

1. Objectives & Contributions2. Introduction

3. Related Work

4. Proposed System

5. Experimental and Results6. Conclusion7. Future Work

Outline

1. Motivations & Objectives & Contributions2. Introduction

3. Related Work

4. Proposed System


Motivations

We developed our low cost demining robot for the following purposes:1-Every landmines detection technique has error rates.

2-The landmines still there, due to the limited performance of available techniques.

3-In the last years, many demining researches used GPR is very expensive ,very heavy ,and power hungry.

Objectives

Designing a low-cost mobile robot.

Proposing a method to detect landmines by integrating

more than one technique.

Using effective motion planning algorithm .

Ensuring the demining operators safety.

Designing an autonomous low cost light mobile robot .

Effective motion planning in mines detection and saves

time.

Using Multisensor fusion in demining.

Developing affective object avoidance algorithm.

We implemented a system uses effective technique to defuse

the mines where they are.

Contributions

Outline


3. Related Work

4. Proposed System


Introduction

There are two types of Landmines:

Anti-personnel(AP): Is an explosive device made to injure or kill a person.

Anti-tank(AT) : AT are designed to destroy tanks and armored vehicles.

Introduction(cont.)

Egypt as a Case Study Egypt has 23 million, mostly in border regions) Egypt suffers alone from more than 20% of the total

number of the landmines in the world. A huge area of land is affected about 25,000 sq.

kilometers.

Introduction(cont.)

Technologies are used for landmine detection are: Humanitarian demining1. Metal detector2. Dogs 5-Bactria3. Rats 6-Plants

4. Honey bees

Mechanical clearance

Advanced electromagnetic methods

1. Ground penetrating radar

2. Nuclear detection

3. Acoustic detection

4. Biological sensors

5. Chemical sensors such as thermal fluorescence

Introduction(cont.)

Technologies Comparison:

Outline


3. Related Work

4. Proposed System


Related Work

Akhtar [2012] Used GPR to captures an image in real-time.

• Fed into a processing unit where smaller segments of it, analyzed after being processed for noise reduction.

• Then recognized and classified landmines with success rate 90%

• This scheme has some drawbacks:• The sensor such as GPR is larger and heavier.• GPR is more power hungry.• GPR can suffer falls alarm rates as high as metal

detectors.

Related Work (cont.)

Ghribi et al. [2013] developed a cheap wheeled robot that could detect only metal mines.

The robot mounted on a metal detector to detect mines.

The system used to color paint to mark the position of detected mines. This scheme has some drawbacks:

high false alarms due to metal objects in the soil.

Related Work (cont.)

Garcia et al [2002] proposed awaking robot for detecting and locating antipersonnel landmines, consisted of: ahead with detector, locator with GPS.• The robot was controlled remotely • There is some drawback in their scheme,

such asHigh costThe robot can be triggeredFalse alarms

Outline


3. Related Work

4. Proposed System


The proposed system depends on two main things: 1. Motion planning

Complete coverage algorithm.2. Sensors fusion using decision level

Preprocessing receive alarms Count alarms

EstimationComputing send Information

Landmines destroying

The Proposed System

The Proposed System(cont.)The block diagram for Demining system

The Proposed System(cont.)1.Motion planning

Motion planning: complete coverage algorithmDecompose the field into cells

The Proposed System(cont.)Complete coverage in parallel method

Motion planning: complete coverage algorithmDecompose the field into cells

The Proposed System(cont.)2. Multi-sensor fusion

By using Decision level fusion

The Proposed System(cont.)Multi-sensor fusion(Decision Level fusion)

then this is a mine.

The Proposed System(cont.)

The generic decision-level sensor-fusion layout

The Proposed System(cont.)Cheap sensors comparison

The Proposed System(cont.)Multi-sensor fusion flow chart

The Proposed System(cont.)3. Defusing mines

The proposed technique is using Robot arm to defuse mines in their locations by locating a ticking time bombs in places mines

Outline1. Objectives & Contributions2. Introduction

3. Related Work

4. Proposed System


Experimental results Autonomous robot structure

low cost equipped vehicle, multiple simple machines are used, each one carrying a very limited amount of mine detection.

Experimental results The system structure

Experimental results

Fake mines simulation

Experimental results Robot Simulation

Experimental results Environment test.

Experimental results Results

summary.

Outline

1. Objectives & Contributions2. 3D Object Recognition

3. Related Work

4. Proposed System


Conclusion

Conclusion(cont.)

• The robot uses a coverage algorithm technique where explicitly passes over all points in the minefield at least once.

• The algorithm guarantees complete coverage of unknown areas for ensuring the detected mines existence.

• The experimental results proved that using multisensor system using decision level fusion when robot move in coverage based motion decreased the false alarms.

Conclusion(cont.)

• Our Result proved that using more than one low-cost sensors is better than using the best sensor alone.

• Demining can be done with very low cost with only $140.

• The overall demining process has no risks to a human operator with using very small and light sensors.

Conclusion(cont.)

• The more obstacles are in the field; the

longer time the overall process takes.

• So Using fails to clean the field from

obstacles before demining is a critical step.

• using many robots with the same design,

which work together in parallel way solved

the time problem

Conclusion(cont.)

• The robot can detect landmines with high

detection rates.

• The use of multi-sensor fusion solved the

problem of high rates of false alarms of

demining sensors.

• Destroying the mines where they are, is

better than forming maps of found mines

and then defusing them.

Outline


3. Related Work

4. Proposed System


using one expensive metal detector sensor that will be better

to increase detection distance underground more than 60 cm.

Test the robot in real mines field

I suggest for the new researchers in demining try to use

nanotechnology or Either that will increase the efficiency of

landmines detection.

Using crawler robot will be better than wheels robots in

demining process.

Testing the robot in real environments.

Future Work

A. Ismail, M. Elmogy, H. ElBakry, " Landmines Detection Using Autonomous Robots: A Survey", International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 3, Issue 4, 4, July-August 2014.

A. Ismail, M. Elmogy, H. ElBakry, "Landmines Detection Using Low-Cost Multisensory Mobile Robot", Journal of Convergence Information Technology, Volume 3, Issue 4, 2015.

Publications

References

• Y.Baudoin, and I.Doroftei," TriDem-A Wheeled Mobile Robot for Humanitarian Mine Clearance", Citeseer, 2012

• A.Muhammad, S. Abbas, T.Manzoor,A. Munawar,S. Abbas,M. Hayat,A. Abbas,and M.Awais," Marwa: A rough terrain landmine detection robot for low budgets",cyphynets.lums.edu.pk,2012.

• A.Alshbatat," Behavior-Based Approach for the Detection of Land Mines Utilizing off the Shelf Low Cost Autonomous Robot",IAES International Journal of Robotics and Automation (IJRA),2,83-92,2013

• G.Tesfamariam, "Signal Processing Techniques for Landmine Detection Using Impulse Ground Penetrating Radar (ImGPR)", TU Darmstadt, 2013