Adaptive navigation and motion planning for a mobile track robot

B. H. Sudantha, K. A.S.N. Sumathipala, C. Premachandra, K. M.H.K. Warnakulasooriya, C. S. Elvitigala, Y. P. Jayasuriya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Localization and navigation of mobile robots precisely in an indoor environment is one of most important and challenging tasks. Navigation using conventional approaches such as Global Positioning System (GPS) and some vision based odometry are not very much effective in indoor environments. Therefore, a magnetic wheel encoding mechanism was selected in order to improve the navigational method. Also it could be with the most common localization approaches such as GPS, inertial navigation systems and laser sensors. This paper discusses a mobile robot application which navigates using magnetic wheel encoders and camera sensor. Further, the robot uses Wi-Fi to gather information and it creates intelligence to find the path dynamically. The Central control center and its main database process all available data and send the relevant control commands to the robots. Additionally, it will direct the messages between the nodes and the robot and keep robots on the correct track. The environment that the robot is moving is a pulse of black lines in white background. For the detection of the line Hough transformation has been used. It is having the capability of detecting sensor nodes using Radio-frequency identification (RFID) or Quick Response (QR) codes and taking measurements and returning to the base station avoiding obstacles communicating between nodes and the base.

LanguageEnglish
Title of host publicationIFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509049172
DOIs
StatePublished - 2017 Aug 30
Event17th Joint World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, IFSA-SCIS 2017 - Otsu, Japan
Duration: 2017 Jun 272017 Jun 30

Other

Other17th Joint World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, IFSA-SCIS 2017
CountryJapan
CityOtsu
Period17/6/2717/6/30

Fingerprint

Motion planning
Navigation
Robots
Mobile robots
Global positioning system
Wheels
Robot applications
Wi-Fi
Inertial navigation systems
Sensors
Radio frequency identification (RFID)
Sensor nodes
Base stations
Cameras
Lasers

Keywords

  • Localization
  • Magnetic Odometry
  • Mobile Track Robot
  • Navigation
  • Wheel Encoders

ASJC Scopus subject areas

  • Logic
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

Cite this

Sudantha, B. H., Sumathipala, K. A. S. N., Premachandra, C., Warnakulasooriya, K. M. H. K., Elvitigala, C. S., & Jayasuriya, Y. P. (2017). Adaptive navigation and motion planning for a mobile track robot. In IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems [8023304] Institute of Electrical and Electronics Engineers Inc.. DOI: 10.1109/IFSA-SCIS.2017.8023304

Adaptive navigation and motion planning for a mobile track robot. / Sudantha, B. H.; Sumathipala, K. A.S.N.; Premachandra, C.; Warnakulasooriya, K. M.H.K.; Elvitigala, C. S.; Jayasuriya, Y. P.

IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems. Institute of Electrical and Electronics Engineers Inc., 2017. 8023304.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sudantha, BH, Sumathipala, KASN, Premachandra, C, Warnakulasooriya, KMHK, Elvitigala, CS & Jayasuriya, YP 2017, Adaptive navigation and motion planning for a mobile track robot. in IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems., 8023304, Institute of Electrical and Electronics Engineers Inc., 17th Joint World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, IFSA-SCIS 2017, Otsu, Japan, 17/6/27. DOI: 10.1109/IFSA-SCIS.2017.8023304
Sudantha BH, Sumathipala KASN, Premachandra C, Warnakulasooriya KMHK, Elvitigala CS, Jayasuriya YP. Adaptive navigation and motion planning for a mobile track robot. In IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems. Institute of Electrical and Electronics Engineers Inc.2017. 8023304. Available from, DOI: 10.1109/IFSA-SCIS.2017.8023304
Sudantha, B. H. ; Sumathipala, K. A.S.N. ; Premachandra, C. ; Warnakulasooriya, K. M.H.K. ; Elvitigala, C. S. ; Jayasuriya, Y. P./ Adaptive navigation and motion planning for a mobile track robot. IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems. Institute of Electrical and Electronics Engineers Inc., 2017.
@inproceedings{b9b027872ea94dccad92a901b0321398,
title = "Adaptive navigation and motion planning for a mobile track robot",
abstract = "Localization and navigation of mobile robots precisely in an indoor environment is one of most important and challenging tasks. Navigation using conventional approaches such as Global Positioning System (GPS) and some vision based odometry are not very much effective in indoor environments. Therefore, a magnetic wheel encoding mechanism was selected in order to improve the navigational method. Also it could be with the most common localization approaches such as GPS, inertial navigation systems and laser sensors. This paper discusses a mobile robot application which navigates using magnetic wheel encoders and camera sensor. Further, the robot uses Wi-Fi to gather information and it creates intelligence to find the path dynamically. The Central control center and its main database process all available data and send the relevant control commands to the robots. Additionally, it will direct the messages between the nodes and the robot and keep robots on the correct track. The environment that the robot is moving is a pulse of black lines in white background. For the detection of the line Hough transformation has been used. It is having the capability of detecting sensor nodes using Radio-frequency identification (RFID) or Quick Response (QR) codes and taking measurements and returning to the base station avoiding obstacles communicating between nodes and the base.",
keywords = "Localization, Magnetic Odometry, Mobile Track Robot, Navigation, Wheel Encoders",
author = "Sudantha, {B. H.} and Sumathipala, {K. A.S.N.} and C. Premachandra and Warnakulasooriya, {K. M.H.K.} and Elvitigala, {C. S.} and Jayasuriya, {Y. P.}",
year = "2017",
month = "8",
day = "30",
doi = "10.1109/IFSA-SCIS.2017.8023304",
language = "English",
booktitle = "IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

TY - GEN

T1 - Adaptive navigation and motion planning for a mobile track robot

AU - Sudantha,B. H.

AU - Sumathipala,K. A.S.N.

AU - Premachandra,C.

AU - Warnakulasooriya,K. M.H.K.

AU - Elvitigala,C. S.

AU - Jayasuriya,Y. P.

PY - 2017/8/30

Y1 - 2017/8/30

N2 - Localization and navigation of mobile robots precisely in an indoor environment is one of most important and challenging tasks. Navigation using conventional approaches such as Global Positioning System (GPS) and some vision based odometry are not very much effective in indoor environments. Therefore, a magnetic wheel encoding mechanism was selected in order to improve the navigational method. Also it could be with the most common localization approaches such as GPS, inertial navigation systems and laser sensors. This paper discusses a mobile robot application which navigates using magnetic wheel encoders and camera sensor. Further, the robot uses Wi-Fi to gather information and it creates intelligence to find the path dynamically. The Central control center and its main database process all available data and send the relevant control commands to the robots. Additionally, it will direct the messages between the nodes and the robot and keep robots on the correct track. The environment that the robot is moving is a pulse of black lines in white background. For the detection of the line Hough transformation has been used. It is having the capability of detecting sensor nodes using Radio-frequency identification (RFID) or Quick Response (QR) codes and taking measurements and returning to the base station avoiding obstacles communicating between nodes and the base.

AB - Localization and navigation of mobile robots precisely in an indoor environment is one of most important and challenging tasks. Navigation using conventional approaches such as Global Positioning System (GPS) and some vision based odometry are not very much effective in indoor environments. Therefore, a magnetic wheel encoding mechanism was selected in order to improve the navigational method. Also it could be with the most common localization approaches such as GPS, inertial navigation systems and laser sensors. This paper discusses a mobile robot application which navigates using magnetic wheel encoders and camera sensor. Further, the robot uses Wi-Fi to gather information and it creates intelligence to find the path dynamically. The Central control center and its main database process all available data and send the relevant control commands to the robots. Additionally, it will direct the messages between the nodes and the robot and keep robots on the correct track. The environment that the robot is moving is a pulse of black lines in white background. For the detection of the line Hough transformation has been used. It is having the capability of detecting sensor nodes using Radio-frequency identification (RFID) or Quick Response (QR) codes and taking measurements and returning to the base station avoiding obstacles communicating between nodes and the base.

KW - Localization

KW - Magnetic Odometry

KW - Mobile Track Robot

KW - Navigation

KW - Wheel Encoders

UR - http://www.scopus.com/inward/record.url?scp=85030836146&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85030836146&partnerID=8YFLogxK

U2 - 10.1109/IFSA-SCIS.2017.8023304

DO - 10.1109/IFSA-SCIS.2017.8023304

M3 - Conference contribution

BT - IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems

PB - Institute of Electrical and Electronics Engineers Inc.

ER -