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All Journal IAES International Journal of Robotics and Automation (IJRA) Indonesian Journal of Electrical Engineering and Computer Science
Kuldeep S. Rawat
Elizabeth City State University
Automotive Engineering Electrical & Electronics Engineering

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From CAD to Robot: Undergraduate Capstone Design in Engineering Technology Kuldeep S. Rawat; G.H. Massiha
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 4: December 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (870.746 KB) | DOI: 10.11591/ijra.v2i4.pp140-148

Abstract

A novel senior project in designing and implementing a wheeled platform-based experimental mobile robot is discussed. This mobile robot design project was used as a platform to learn sensor interfacing, microcontroller programming, motor control, and electronic circuit design and troubleshooting. A specially designed proto board was used so that students could experiment with various types of sensors and supporting electronic circuitry. The modules implemented in this project are, servo motor control, infrared (IR)-based obstacle detection and avoidance, temperature sensing, and IR wireless communication. An 8-bit Peripheral Interface Controller (PIC) microcontroller, operating at 20MHz, was used as a programmable controller to monitor external environment through sensors and make appropriate decisions. PIC microcontroller was programmed using PICBasic PRO, a BASIC like high-level language. The implementation was divided into separate experiments, through which the students progressively completed the mobile robot. This progressive experimentation helped students develop their knowledge of interfacing, microcontroller programming, electronic control, circuit design, and troubleshooting in an incremental manner. The robot design experiments, sensor interfacing, electronic control, supporting circuitry, problems faced and troubleshooting during implementation are discussed in the paper.
Hardware Implementation of FIR Neural Network for Applications in Time Series Data Prediction Kuldeep S. Rawat; G.H. Massiha
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2015
Publisher : Institute of Advanced Engineering and Science

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Abstract

Time series data prediction is used in several applications in the area of science and engineering. Time series prediction models have been implemented using statistical approaches, but recently, neural networks are being applied for times series prediction due to their inherent properties and capabilities. A variation of a standard neural network called as finite impulse response (FIR) neural network has proven to be highly successful in achieving higher degree of prediction accuracy when used over various time series prediction applications. These applications are time critical and involve huge amounts of computation that are slower when run on a general purpose processor and hence, a dedicated hardware is required. In this paper, authors present hardware implementation of an FIR neural network for applications in times series data prediction. The implementation is divided into (i) off-board, where the training algorithm and neural network configuration is implemented in Matrix Laboratory (MATLAB) and simulated with various benchmark time series data set and (ii) on-board, where the entire system is modeled in a hardware description language (HDL). The simulation experiment, hardware building blocks, the implementation framework, and the hardware design flow are discussed in this paper. The hardware resource utilization and timing information are also reported in the paper. DOI: http://dx.doi.org/10.11591/telkomnika.v14i1.7272 
Co-Authors G.H. Massiha