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.
N1 - Publisher Copyright:
© 2017 IEEE.
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
AN - SCOPUS:85030836146
T3 - IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
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.
T2 - 17th Joint World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, IFSA-SCIS 2017
Y2 - 27 June 2017 through 30 June 2017
ER -