An FPGA-Based Omnidirectional Vision Sensor for Motion Detection on Mobile Robots

This work presents the development of an integrated hardware/software sensor system for moving object detection and distance calculation, based on background subtraction algorithm. The sensor comprises a catadioptric system composed by a camera and a convex mirror that reflects the environment to the camera from all directions, obtaining a panoramic view. The sensor is used as an omnidirectional vision system, allowing for localization and navigation tasks of mobile robots. Several image processing operations such as filtering, segmentation and morphology have been included in the processing architecture. For achieving distance measurement, an algorithm to determine the center of mass of a detected object was implemented. The overall architecture has been mapped onto a commercial low-cost FPGA device, using a hardware/software co-design approach, which comprises a Nios II embedded microprocessor and specific image processing blocks, which have been implemented in hardware. The background subtraction algorithm was also used to calibrate the system, allowing for accurate results. Synthesis results show that the system can achieve a throughput of 26.6 processed frames per second and the performance analysis pointed out that the overall architecture achieves a speedup factor of 13.78 in comparison with a PC-based solution running on the real-time operating system xPC Target.

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A low cost 3D vision system for positioning welding mobile robots using a FPGA prototyping system

IEEE 2002 28th Annual Conference of the Industrial Electronics Society IECON 02 IECON-02 ◽

10.1109/iecon.2002.1185517 ◽

2003 ◽

Cited By ~ 1

Author(s):

I. Ibanez ◽

M.A. Aguirre ◽

A. Torralba ◽

L.G. Franquelo

Keyword(s):

Mobile Robots ◽

Vision System ◽

Low Cost ◽

3D Vision

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Fast and Robust Vision System for Shogi Robot

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2015.p0182 ◽

2015 ◽

Vol 27 (2) ◽

pp. 182-190

Author(s):

Gou Koutaki ◽

◽

Keiichi Uchimura

Keyword(s):

Image Processing ◽

Vision System ◽

Low Cost ◽

Robot Arm ◽

Image Processing Algorithm ◽

Robot System ◽

Cost System ◽

Robot Systems ◽

Web Camera ◽

Lower Frame

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/08.jpg"" width=""150"" />Developed shogi robot system</div> The authors developed a low-cost, safety shogi robot system. A Web camera installed on the lower frame is used to recognize pieces and their positions on the board, after which the game program is played. A robot arm moves a selected piece to the position used in playing a human player. A fast, robust image processing algorithm is needed because a low-cost wide-angle Web camera and robot are used. The authors describe image processing and robot systems, then discuss experiments conducted to verify the feasibility of the proposal, showing that even a low-cost system can be highly reliable. </span>

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1P1-D07 Study on Motion Control for Mobile Robots Using Visual Information : Image Processing for the Forward Course Situation(Vision System for Mobile Robot)

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ◽

10.1299/jsmermd.2014._1p1-d07_1 ◽

2014 ◽

Vol 2014 (0) ◽

pp. _1P1-D07_1-_1P1-D07_2

Author(s):

Masanori KAWASUMI ◽

Noriyasu MASUMOTO

Keyword(s):

Image Processing ◽

Mobile Robot ◽

Mobile Robots ◽

Motion Control ◽

Visual Information ◽

Vision System ◽

Information Image

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Fenômica

International Journal of Agricultural and Environmental Information Systems ◽

10.4018/ijaeis.2020010101 ◽

2020 ◽

Vol 11 (1) ◽

pp. 1-22

Author(s):

Marcos Roberto dos Santos ◽

Guilherme Afonso Madalozzo ◽

José Maurício Cunha Fernandes ◽

Rafael Rieder

Keyword(s):

Image Processing ◽

Computer Vision ◽

Web Application ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Agricultural Research ◽

Vision System ◽

Low Cost ◽

Wheat Crop ◽

Three Solutions

Computer vision and image processing procedures could obtain crop data frequently and precisely, such as vegetation indexes, and correlating them with other variables, like biomass and crop yield. This work presents the development of a computer vision system for high-throughput phenotyping, considering three solutions: an image capture software linked to a low-cost appliance; an image-processing program for feature extraction; and a web application for results' presentation. As a case study, we used normalized difference vegetation index (NDVI) data from a wheat crop experiment of the Brazilian Agricultural Research Corporation. Regression analysis showed that NDVI explains 98.9, 92.8, and 88.2% of the variability found in the biomass values for crop plots with 82, 150, and 200 kg of N ha1 fertilizer applications, respectively. As a result, NDVI generated by our system presented a strong correlation with the biomass, showing a way to specify a new yield prediction model from the beginning of the crop.

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Vision Based Localization for Multiple Mobile Robots Using Low-cost Vision Sensor

International Journal of Handheld Computing Research ◽

10.4018/ijhcr.2016010102 ◽

2016 ◽

Vol 7 (1) ◽

pp. 12-25

Author(s):

Seokju Lee ◽

Girma Tewolde ◽

Jongil Lim ◽

Jaerock Kwon

Keyword(s):

Mobile Robots ◽

Vision System ◽

Low Cost ◽

Vision Sensor ◽

Rf Transceiver ◽

Multiple Mobile Robots ◽

Multiple Devices ◽

Localization Performance ◽

Vision Based Localization ◽

High Flexibility

This paper presents an efficient approach for a vision based localization of multiple mobile robots in an indoor environment by using a low cost vision sensor. The proposed vision sensor system that uses a single camera mounted over the mobile robots field takes advantages of small size, low energy consumption, and high flexibility to play an important role in the field of robotics. The nRF24L01 RF transceiver is connected to the vision system to enable wireless communication with multiple devices through 6 different data pipes. The downward-facing camera provides excellent performance that has the ability to identify a number of objects based on color codes, which form colored landmarks that provide mobile robots with useful image information for localization in the image view, which is then transformed to real world coordinates. Experimental results are given to show that the proposed method can obtain good localization performance in multi-mobile robots setting.

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A target tracking and location robot system based on omnistereo vision

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-03-2017-0042 ◽

2017 ◽

Vol 44 (6) ◽

pp. 741-753 ◽

Cited By ~ 2

Author(s):

Chengtao Cai ◽

Bing Fan ◽

Xiangyu Weng ◽

Qidan Zhu ◽

Li Su

Keyword(s):

Image Processing ◽

Target Tracking ◽

Vision System ◽

Computation Time ◽

Processing Method ◽

Omnidirectional Vision ◽

Robot System ◽

Content Type ◽

Tracking Method ◽

Local Image

Purpose Because of their large field of view, omnistereo vision systems have been widely used as primary vision sensors in autonomous mobile robot tasks. The purpose of this article is to achieve real-time and accurate tracking by the omnidirectional vision robot system. Design/methodology/approach The authors provide in this study the key techniques required to obtain an accurate omnistereo target tracking and location robot system, including stereo rectification and target tracking in complex environment. A simple rectification model is proposed, and a local image processing method is used to reduce the computation time in the localization process. A target tracking method is improved to make it suitable for omnidirectional vision system. Using the proposed methods and some existing methods, an omnistereo target tracking and location system is established. Findings The experiments are conducted with all the necessary stages involved in obtaining a high-performance omnistereo vision system. The proposed correction algorithm can process the image in real time. The experimental results of the improved tracking algorithm are better than the original algorithm. The statistical analysis of the experimental results demonstrates the effectiveness of the system. Originality/value A simple rectification model is proposed, and a local image processing method is used to reduce the computation time in the localization process. A target tracking method is improved to make it suitable for omnidirectional vision system. Using the proposed methods and some existing methods, an omnistereo target tracking and location system is established.

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