scholarly journals Human Following for Outdoor Mobile Robots Based on Point‐Cloud's Appearance Model

2021 ◽  
Vol 30 (6) ◽  
pp. 1087-1095
Author(s):  
GONG Linxi ◽  
CAI Yunfei
Keyword(s):  
Mobile Robots ◽  
Appearance Model

Position and Rotation Estimation for Mobile Robots in Outside of Recording Path Using Ego-motion

2013 ◽  
Vol 133 (2) ◽  
pp. 356-364 ◽  
Author(s):  
Yoshinobu Hagiwara ◽  
Tatsuya Shoji ◽  
Hiroki Imamura
Keyword(s):  
Mobile Robots ◽  
Rotation Estimation

Deployment Control of Wireless Multi-Hop-Relay Mobile Robots Based on Voronoi Partition

2012 ◽  
Vol 132 (3) ◽  
pp. 381-388
Author(s):  
Takaaki Imaizumi ◽  
Hiroyuki Murakami ◽  
Yutaka Uchimura
Keyword(s):  
Mobile Robots ◽  
Voronoi Partition

Time-Optimal Gathering Algorithm of Mobile Robots with Local Weak Multiplicity Detection in Rings

2013 ◽  
Vol E96.A (6) ◽  
pp. 1072-1080 ◽  
Author(s):  
Tomoko IZUMI ◽  
Taisuke IZUMI ◽  
Sayaka KAMEI ◽  
Fukuhito OOSHITA
Keyword(s):  
Mobile Robots ◽  
Time Optimal

Control of Mobile Robots by Means of Internet

2006 ◽  
Vol 65 (3) ◽  
pp. 229-241
Author(s):  
S. F. Yatsun ◽  
F. K. Freire ◽  
V. S. Dyshenko ◽  
O. A. Shadrina
Keyword(s):  
Mobile Robots

Change of color appearance due to extremely high light level: corresponding colors under 100 and 3000 cd/m2

2019 ◽  
Vol 2019 (1) ◽  
pp. 320-325 ◽  
Author(s):  
Wenyu Bao ◽  
Minchen Wei
Keyword(s):  
Light Level ◽  
Limited Range ◽  
High Light ◽  
Color Preference ◽  
Color Appearance ◽  
Appearance Model ◽  
Color Matching ◽  
Light Levels ◽  
Appearance Models ◽  
Psychophysical Study

Great efforts have been made to develop color appearance models to predict color appearance of stimuli under various viewing conditions. CIECAM02, the most widely used color appearance model, and many other color appearance models were all developed based on corresponding color datasets, including LUTCHI data. Though the effect of adapting light level on color appearance, which is known as "Hunt Effect", is well known, most of the corresponding color datasets were collected within a limited range of light levels (i.e., below 700 cd/m2), which was much lower than that under daylight. A recent study investigating color preference of an artwork under various light levels from 20 to 15000 lx suggested that the existing color appearance models may not accurately characterize the color appearance of stimuli under extremely high light levels, based on the assumption that the same preference judgements were due to the same color appearance. This article reports a psychophysical study, which was designed to directly collect corresponding colors under two light levels— 100 and 3000 cd/m2 (i.e., ≈ 314 and 9420 lx). Human observers completed haploscopic color matching for four color stimuli (i.e., red, green, blue, and yellow) under the two light levels at 2700 or 6500 K. Though the Hunt Effect was supported by the results, CIECAM02 was found to have large errors under the extremely high light levels, especially when the CCT was low.

Colour Image Enhancement using Perceptual Saturation and Vividness

2019 ◽  
Vol 2019 (1) ◽  
pp. 243-246
Author(s):  
Muhammad Safdar ◽  
Noémie Pozzera ◽  
Jon Yngve Hardeberg
Keyword(s):  
Image Quality ◽  
Image Enhancement ◽  
Test Performance ◽  
Appearance Model ◽  
Colour Space ◽  
Categorical Judgment ◽  
Saturation Scale ◽  
Colour Image ◽  
Colour Appearance ◽  
Future Test

A perceptual study was conducted to enhance colour image quality in terms of naturalness and preference using perceptual scales of saturation and vividness. Saturation scale has been extensively used for this purpose while vividness has been little used. We used perceptual scales of a recently developed colour appearance model based on Jzazbz uniform colour space. A two-fold aim of the study was (i) to test performance of recently developed perceptual scales of saturation and vividness compared with previously used hypothetical models and (ii) to compare performance and chose one of saturation and vividness scales for colour image enhancement in future. Test images were first transformed to Jzazbz colour space and their saturation and vividness were then decreased or increased to obtain 6 different variants of the image. Categorical judgment method was used to judge preference and naturalness of different variants of the test images and results are reported.

Polygon Shape Formation for Multi-Mobile Robots in a Local Knowledge Environment

2019 ◽  
Vol 19 (2) ◽  
pp. 39-46
Author(s):  
Abdulmuttalib T. Rashid ◽  
Abduladhem A. Ali
Keyword(s):  
Mobile Robots ◽  
Local Knowledge ◽  
Shape Formation ◽  
Knowledge Environment

An Obstacle-resistant Relay Node Placement in Constrained Environment

2019 ◽  
Author(s):  
Abhishek Verma ◽  
Virender Ranga
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Robots ◽  
Relay Node ◽  
Wireless Sensor ◽  
Relay Node Placement ◽  
Node Placement ◽  
Simulation Results ◽  
Additional Hardware ◽  
Shape And Size

Relay node placement in wireless sensor networks for constrained environment is a critical task due to various unavoidable constraints. One of the most important constraints is unpredictable obstacles. Handling obstacles during relay node placement is complicated because of complexity involved to estimate the shape and size of obstacles. This paper presents an Obstacle-resistant relay node placement strategy (ORRNP). The proposed solution not only handles the obstacles but also estimates best locations for relay node placement in the network. It also does not involve any additional hardware (mobile robots) to estimate node locations thus can significantly reduce the deployment costs. Simulation results show the effectiveness of our proposed approach.

Sign in / Sign up

Export Citation Format

Share Document