This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481980 | PMC |
http://dx.doi.org/10.3390/s150511208 | DOI Listing |
Front Immunol
December 2024
School of Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Background: Thyroid-associated orbitopathy (TAO) is an autoimmune inflammatory disorder of the orbital adipose tissue, primarily causing oxidative stress injury and tissue remodeling in the orbital connective tissue. Ferroptosis is a form of programmed cell death driven by the accumulation of reactive oxygen species (ROS), iron metabolism disorder, and lipid peroxidation. This study aims to identify and validate the optimal feature genes (OFGs) of ferroptosis with diagnostic and therapeutic potential in TAO orbital adipose tissue through bioinformatics analysis and to assess their correlation with disease-related immune cell infiltration.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2024
School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
Background: Osteoporotic vertebral compression fractures (OVCFs) are the most common type of fragility fracture. Distinguishing between OVCFs and other types of vertebra diseases, such as old fractures (OFs), Schmorl's node (SN), Kummell's disease (KD), and previous surgery (PS), is critical for subsequent surgery and treatment. Combining with advanced deep learning (DL) technologies, this study plans to develop a DL-driven diagnostic system for diagnosing multi-type vertebra diseases.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
October 2023
In this article, we provide a comprehensive study of a new task called collaborative camouflaged object detection (CoCOD), which aims to simultaneously detect camouflaged objects with the same properties from a group of relevant images. To this end, we meticulously construct the first large-scale dataset, termed CoCOD8K, which consists of 8528 high-quality and elaborately selected images with object mask annotations, covering five superclasses and 70 subclasses. The dataset spans a wide range of natural and artificial camouflage scenes with diverse object appearances and backgrounds, making it a very challenging dataset for CoCOD.
View Article and Find Full Text PDFJ Med Internet Res
June 2023
Department of Primary and Community Care, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, Netherlands.
Background: Intimate partner violence and abuse (IPVA) is a pervasive societal issue that impacts many women globally. Web-based help options are becoming increasingly available and have the ability to eliminate certain barriers in help seeking for IPVA, especially in improving accessibility.
Objective: This study focused on the quantitative evaluation of the SAFE eHealth intervention for women IPVA survivors.
Indian J Otolaryngol Head Neck Surg
September 2022
Department of Prosthodontics, Centre for Dental Education and Research, AIIMS, New Delhi, India.
Abstract: The purpose of the study was to assess psychological status (PS) and quality of life (QOL) before surgical resection of maxilla (T0), 2 weeks after resection (T1), 2 weeks after use of intermediate obturator (T2), before (T3) and 12 weeks after use of definitive obturator (T4). 20 participants, planned for resection of maxilla and subsequent prosthodontic rehabilitation were enrolled. Assessment was done using Hospital Anxiety and Depression Scale (HADS) (HADS-A: anxiety and HADS-D: depression) for PS, World Health Organization Quality of Life BREF (WHOQOL-BREF) and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire- Head and Neck Module (EORTC QLQ- H&N35) for QOL, and obturator functioning scale (OFS) for obturator functioning.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!