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This research paper outlines the Malaysian and Japanese undergraduate students' learning motivation, before and after joining a Global Study Program (GSP) held in Chiba University, Japan from 14 March-28 March 2016. A total of 15 Malaysian undergraduate students from Multimedia University, consisting of 2nd year to 4th year students, joined the GSP together with 15 Japanese 1st year to 4th year undergraduate students from Chiba University. The study focused on examining students' learning motivation in three experiment phases. The 1st phase of experiment consisted of conducting surveys on all students before the commencement of GSP. The 2nd phase of experiment consisted of daily observational measurements toward students' motivation and performance. Lastly, the 3rd phase of experiment consisted of conducting the same surveys again on all students after the GSP. Note that the survey consisted of 29 questions covering value components, expectancy components, affective components and self-perceived learning components. The results of this study indicated that the learning motivation of Malaysian and Japanese undergraduate students had significantly improved after joining the GSP course.

Research toward unmanned mobile robot navigation has gained significant importance in the last decade due to its potential applications in the location-based services industry. The increase in construction of large space indoor buildings has made difficulty for humans to operate within such environments. In this study, a mobile robot's indoor navigation algorithm is developed with vision cameras. Using two monocular cameras (one looking forward and one looking downward), the developed algorithms make use of the salient features of the environments to estimate rotational and translational motions for real-time positioning of the mobile robot. At the same time, an algorithm based on artificial landmark recognition is developed. The artificial landmark is shaped arrow based signboards with different colors representing different paths. These algorithms are integrated into a designed framework for mobile robot real-time positioning and autonomous navigation. Experiments are performed to validate the designed system using the mobile robot PIONEER P3-AT. The developed algorithm was able to detect and extract artificial landmark information up to 3 m distance for the mobile robot guidance. Experiment results show an average error of 0.167 m deviation from the ideal path, signified the good ability and performance of the development autonomous navigation algorithm.

Over the past few decades due to the advancement of technology, biometrics has evolved into a key factor of security for societal needs. Biometrics started as a basic ID verification system and has evolved into a major factor of authentication by taking several biological parameters as references. There are certain issues that researchers have yet been facing against hack or overriding. This chapter covers a comparative study of different biometrics and its methods used for safe authentication that improves security management for complicated scenarios.

This paper presents the design and development of a PC-based orientation sensing system using strapdown inertial measurement unit (SIMU). A 9-DOF (degree of freedom) SIMU, which consists of 3-DOF gyroscopes, 3-DOF accelerometers, and 3-DOF magnetometers, are used to estimate the orientation. Data fusion is performed to improve measurement accuracy. In this paper, the orientation measurements are compared and discussed using three different approaches, known as the conventional accelerometer/gyroscope approach, the Kalman filter based 9-DOF SIMU approach, and the gradient decent algorithm based 9-DOF SIMU approach. The derivation of each approach together with the design of the PC-based orientation sensing system is outlined in this paper.

This paper proposed A Star (A∗) Path Following (APF) Mobile Robot with Intelligent Path Mapping (IPM) visual interface program in Windows operating system environment. A microcontroller-based APF wheeled mobile robot is developed. A computer Graphical User Interface (GUI) is created with A∗ algorithm — the algorithm widely used for path finding and graph traversal, integrated to develop the IPM visual interface. The GUI maps the optimum path from a starting location to a goal using the A∗ algorithm integrated and generates a series of instructions, where the APF robot is able to communicate, download, store and process instructions from the GUI. Execution of instructions can be done by the APF robot alone afterwards.

This paper describes the interfacing of the biped robot KHR-1 with DSP board TMS320F2812. In this study, the KHR-1 is modeled as a seven-link biped, with each joint connected with a servomotor KRS-784 ICS. The I/O port of the DSP board provides PWM signals to the biped joints for joint control. TMS320F2812 is chosen due to its high PWM resolution as well as its flexibility in PWM frequency setting. The computed joint trajectories of the biped robot are based on the Zero Moment Point (ZMP) model. Walking trajectories are constructed and tested, and the results are beneficial to both biped research as well as mechatronics education for undergraduates.