INT J APPL ELECTR PHYS & ROBOT, Vol. 1 No. 1 July (2013) pp. 10–13 ISSN: 2203-0069 International Journal of Applied Electronics in Physics & Robotics Research-in-Progress Path and Position Monitoring Tool for Indoor Robot Application Ata Jahangir Moshayedi 1, * , Damayanti Chandrashekar Gharpure 1 (1) Department of Electronic Science, University of Pune, Pune: 411007, India. Copyright © 2013 Australian International Academic Centre, Australia doi:10.7575/aiac.ijaepr.v.1n.1p.10 Article history: Received 18 May 2013 Reviewed 26 May 2013 Revised 28 June 2013 Accepted 30 June 2013 Published 8 July 2013 Abstract. Robot position monitoring and navigation with ease of use and implementation is a challenge for researchers. The Path and Position Monitoring system (PPMS) is designed for the robot Platform Mokhtar. The path followed by the robot during experimentation, is acquired and displayed graphically using PPMS. The System provides a log of the location (x, y), movement velocity, number of steps for each movement, along with the date and time as a text file. The data can be used to obtain the velocity and movement trajectory of robot for further study. The PPMS can be used for navigation or any other application in robotic studies. The paper presents the design and development of the system and its use in path monitoring of an autonomous wind tracking robot. Various experiments carried out and the results obtained are discussed. Keywords: PPMS, Path and Position Monitoring system, odometry, robot navigation. 1 Introduction Continuous robot position and path monitoring are a requirement in mobile robotics [1–3] . In general, Robot po- sition and navigation can be categorized into three types of Global, determining the robot position in absolute or map–referenced terms, Local, based on robot position rel- ative to objects and Personal takes into account the posi- tion of various parts, their relative positions for handling objects [2] . Amongst mentioned methods personal and lo- cal navigation are used more for micro robots [2] but self– positioning is more in demand in all research [4–6] . Gao and Tseng proposed self–positioning method to measure the distance and orientation of the robot by a sensor, relative to the previous point as it moves toward the target [3] . One of the famous methods in self–positioning is intro- ducing a landmark as a reference point. Lin and Chen proposed two–dimensional (2D) barcode landmark (as reference) which includes the absolute position and has more abilities or error correction automatically [7] . For automatic indoor positioning and orientation, the land- marks are placed on the robot and the camera takes pictures of them. Landmark angle and position are ac- quired, through image segmentation, contour extraction, curves matching characteristics to compute the robot’s existing absolute position and heading angle. Zeungnam et al. studied the 3D self–positioning for a mobile robot with a set of some guide points using vision(stereo camera) and proposed triple guide points * Corresponding author: A.J. Moshayedi : +91 20 2569 9841 : moshayedi@electronics.unipune.ac.in work well for walking robot with a stereo camera in a laboratory environment [8] . On the other hand, for posi- tion estimation in addition to Vision based methods, some method like odometry sensor (ultrasonic, infra–red), iner- tial navigation [3] dead reckoning, etc. are also reported. The main problem of the above method is due to drift in response with time which affects the accuracy of esti- mation, especially for ultrasonic and infra–red sensor by the instability in the environment leading to false reflec- tion and echoes [2] . Commonly the odometry and inertial navigation methods use active beacons based on artifi- cial landmark recognition, natural landmark recognition, model matching for global position monitoring [5] . Orien- tation and position detection methods based on precise references like the lasers or encoders, in most of the cases are accurate but have the drawback of restriction in ob- ject movements [3,9] . Odometry method using encoder for position monitor- ing is more reliable and recently researchers tried to find a low cost solution [9–11] using the optical mouse. This op- tical mouse sensor overcomes the common problem with position monitoring [12] : 1. Wheels slipping (by not generating the proper mo- tion of the robot) 2. Crawling (not measuring the robot motion by incre- mental encoder). Optical mouse cost and availability, inspire the re- searcher to do some modification and used it in ROBOCUP matches. The modified optical mouse with the help of microcontroller and SPI interfaces used as a tool for robot positing. The performance of their modified optical mouse on different surfaces has been reported [13] .