An Embedded System Design to Build Real-Time 2D Maps for Unknown Indoor Environments

Abstract

This paper presents a remotely controllable, differentially driven wheeled mobile robot development in order to build 2D maps for unknown indoor environments. This system would eliminate the need to preexplore such environments. Main aim of the study is to develop a system with high accuracy by using minimum number of sensors and a processor with low cost especially for comparatively small indoor areas. The distance traveled was calculated using the wheel odometry method. Obstacles surrounding the robot, the distance traveled, and the robot's orientation were obtained using an ultrasonic distance sensor, optical encoder, and a 3D orientation sensor (also known as an Attitude and Heading Reference System-AHRS), respectively. In addition, the characteristics of the system hardware components were empirically explored, and the errors resulting from the sensors were evaluated. The non-linearity percentage error arising from the encoder was defined and then compensated for. The hysteresis behavior of the ultrasonic distance sensors was also empirically tested. All of the tasks were conducted by using a low-cost FPGA (Field Programmable Gate Arrays) board. A graphical development platform of National Instruments (NI) LabVIEW and its FPGA Module was preferred in the study for embedded system programming instead of the text-based HDLs (Hardware Description Languages). This distinguishes the proposed system from similar prior studies.

Zigbee Wireless Network-Based Indoor Mobile Robot Monitoring and Positioning Method Under Binocular Vision

“…Figure 7 is a schematic diagram of the actual measurement of parameter A. The RSSI value of the signal transmitted by the central node O is measured at points A, B, C, and D, and the average value is taken [13][14][15][16][17]. To reduce the complexity of hardware implementation, the CC2431 positioning engine uses the indirect value n sub instead of the parameter n. The value range of n_sub is 0-31.…”

VHDL ile NIBP, SpO2 ve ETCO2 Yaşamsal Sinyallerin FPGA Tabanlı Tasarımı ve Gerçek Zamanlı Uygulaması

“…FPGA çipleri, hızlı ilk üretim, tekrar tekrar programlanabilme, paralel sinyal işleme ve düşük güç tüketimi gibi üstünlüklere sahip olduğundan diğer sayısal sinyal işleme platformlarına göre daha fazla tercih edilmektedir. Her geçen gün kullanım alanı artan FPGA çipleri gömülü sistem [1], haberleşme [2], kriptoloji [3], rasgele sayı üreteçleri [4], kontrol [5], görüntü işleme [6], otomotiv [7], yapay zekâ ve uygulamaları [8], [9], nonlineer osilatörler [10], tüketici elektroniği [11], enerji [12], savunma sanayi [13],…”