Vision-Based Mobile Robot Self-localization and Mapping System for Indoor Environment

Localizing accurately and building map of an environment concurrently is a key factor of a mobile robot system. In this system, the robot makes localization and mapping with artificial landmarks and map-based system. It is a process by which a mobile robot can build a map of an environment while continuously determining the location of the robot within the map. The system estimates the robot position in indoor environments using sensors; a camera, three ultrasonic sensors and encoders. The main contribution of this paper is to reduce computational time and improve mapping with map-based system. The self-localization of mobile robot in an indoor environment is advanced through the construction of map based on sensors and recognition of artificial landmarks. Vision based localization system can benefit from using with ultrasonic sensors. From captured images, the system makes landmark detection by using Canny edge detection and Chain-code Approximation algorithms to represent the contour of landmarks by using edge points. The Kalman filter is aimed to accurately estimate position and orientation of the robot using relative distances to walls or artificial landmarks in environments. A robotic system is capable of mapping in an indoor environment and localizing with respect to the map, in real time, using artificial landmarks and sensors

Tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi MARA terhadap mata pelajaran Bahasa Inggeris

Kajian ini dilakukan untuk mengenal pasti tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi Mara Sri Gading terhadap Bahasa Inggeris. Kajian yang dijalankan ini berbentuk deskriptif atau lebih dikenali sebagai kaedah tinjauan. Seramai 325 orang pelajar Diploma in Construction Technology dari Kolej Kemahiran Tinggi Mara di daerah Batu Pahat telah dipilih sebagai sampel dalam kajian ini. Data yang diperoleh melalui instrument soal selidik telah dianalisis untuk mendapatkan pengukuran min, sisihan piawai, dan Pekali Korelasi Pearson untuk melihat hubungan hasil dapatan data. Manakala, frekuensi dan peratusan digunakan bagi mengukur penguasaan pelajar. Hasil dapatan kajian menunjukkan bahawa tahap penguasaan Bahasa Inggeris pelajar adalah berada pada tahap sederhana manakala faktor utama yang mempengaruhi penguasaan Bahasa Inggeris tersebut adalah minat diikuti oleh sikap. Hasil dapatan menggunakan pekali Korelasi Pearson juga menunjukkan bahawa terdapat hubungan yang signifikan antara sikap dengan penguasaan Bahasa Inggeris dan antara minat dengan penguasaan Bahasa Inggeris. Kajian menunjukkan bahawa semakin positif sikap dan minat pelajar terhadap pengajaran dan pembelajaran Bahasa Inggeris semakin tinggi pencapaian mereka. Hasil daripada kajian ini diharapkan dapat membantu pelajar dalam meningkatkan penguasaan Bahasa Inggeris dengan memupuk sikap positif dalam diri serta meningkatkan minat mereka terhadap Bahasa Inggeris dengan lebih baik. Oleh itu, diharap kajian ini dapat memberi panduan kepada pihak-pihak yang terlibat dalam membuat kajian yang akan datang

Multi-Sensor Localization and Navigation for Remote Manipulation in Smoky Areas

Abstract When localizing mobile sensors and actuators in indoor  environments  laser  meters,  ultrasonic  meters  or  even image processing techniques are usually used. On  the  other  hand,  in  smoky  conditions,  due  to  a  fire  or  building collapse, once the smoke or dust density grows,  optical  methods  are  not  efficient  anymore.  In  these  scenarios  other  type  of  sensors  must  be  used,  such  as  sonar,  radar  or  radiofrequency  signals.  Indoor  localization in low‐visibility  conditions due to  smoke is  one of the EU GUARDIANS [1] project goals.   The developed method aims to position a robot in front  of doors, fire extinguishers and other points of interest  with  enough  accuracy  to  allow  a  human  operator  to  manipulate the robot’s arm in order to actuate over the  element.  In  coarse‐grain  localization,  a  fingerprinting technique  based  on  ZigBee  and  WiFi  signals  is  used,  allowing  the robot  to  navigate  inside  the  building  in  order  to  get  near  the  point  of  interest  that  requires  manipulation.  In  fine‐grained  localization  a  remotely  controlled  programmable  high  intensity  LED  panel  is  used, which acts as a reference to the system in smoky  conditions.  Then,  smoke  detection  and  visual  fine‐ grained localization are used to position the robot with  precisely in the manipulation point (e.g., doors, valves,  etc.)

ALO: An ultrasound system for localization and orientation based on angles

This is the author’s version of a work that was accepted for publication in Microelectronics Journal. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Microelectronics Journal, Vol 44, Issue 10, (October 2013). http://dx.doi.org/10.1016/j.mejo.2013.01.001This paper presents a low cost system based on ultrasound transducers to obtain the localization and orientation information of a mobile node, such as a robot, in a 2D indoor space. The system applies a new differential time of arrival (DTOA) technique with reduced computational cost, which is called ALO (angle localization and orientation). Instead of directly calculating its position, the system calculates the direction of arrival of the received ultrasonic signal and, through it, its position and orientation. A prototype of a robot has been built in order to show the validity of the method through experimental results

The Application of an Hybrid Trilateration Method for Multi-Robot Localization System

The ability to know the location (localization) of robots in the environment or other robots, play an important role in multi-robot systems. Many methods and sensors had been propose, for example Dead-Reckoning; GPS; Vision based; etc.. Dead-Reckoning produce an accumulation errors, if used in a wide area or in a long time moving[1]. GPS has a level of significant errors when applied to a small robot or on the environment that are not large [2], while the vision has a poor response when applied to a fast-moving robots [3]. This research applied the trilaterasi methods that have been commonly used in communications systems, for localization in a multi-robot system composed of robots +11 cm in diameter. Sensors that are used in the form of 3 receiver with relatively fixed position to each other on a robot and an ultrasonic transmitter on the other robots. The principle of measurement based on the arrival time difference, or TDOA and processed by equation trilaterasi [4], to get the distance and relative orientation of the robot. Tests conducted on the condition still and moving the robot, at a certain distance and orientation, with a range of distance measurements between 30cm to 180cm. The result shows that this method successfully applied to the robot, with the average accuracy of 6% in the room, and the average accuracy of 5,2% outside the room. From the results of the analysis is also known that due to lack of the presence of some obstacles, that generate a magnetic field and the significant temperature changes in the robot environment. Another weakness of the system this system can not be used the same sensors (ultrasonic) for the purposes of obstacle detection, because it causes the interference

A noncontact ultrasonic platform for structural inspection

Miniature robotic vehicles are receiving increasing attention for use in nondestructive testing (NDE) due to their attractiveness in terms of cost, safety, and their accessibility to areas where manual inspection is not practical. Conventional ultrasonic inspection requires the provision of a suitable coupling liquid between the probe and the structure under test. This necessitates either an on board reservoir or umbilical providing a constant flow of coupling fluid, neither of which are practical for a fleet of miniature robotic inspection vehicles. Air-coupled ultrasound offers the possibility of couplant-free ultrasonic inspection. This paper describes the sensing methodology, hardware platform and algorithms used to integrate an air-coupled ultrasonic inspection payload into a miniature robotic vehicle platform. The work takes account of the robot's inherent positional uncertainty when constructing an image of the test specimen from aggregated sensor measurements. This paper concludes with the results of an automatic inspection of a aluminium sample