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20 results for “home robot”
Robot@Home2, a robotic dataset of home environments
<p>The Robot-at-Home dataset (<strong>Robot@Home</strong>, paper <a href="http://mapir.uma.es/papersrepo/2017/2017-raul-IJRR-Robot_at_home_dataset.pdf">here</a>) is a collection of raw and processed data from five domestic settings compiled by a mobile robot equipped with 4 RGB-D cameras and a 2D laser scanner. Its main purpose is to serve as a testbed for semantic mapping algorithms through the categorization of objects and/or rooms.</p> <p>This dataset is unique in three aspects:</p> <ul> <li>The provided data were captured with a rig of 4 RGB-D sensors with an overall field of view of 180°H. and 58°V., and with a 2D laser scanner.</li> <li>It comprises diverse and numerous data: <em>sequences of RGB-D images and laser scans</em> from the rooms of five apartments (87,000+ observations were collected), <em>topological information</em> about the connectivity of these rooms, and <em>3D reconstructions</em> and <em>2D geometric maps</em> of the visited rooms.</li> <li>The provided ground truth is dense, including <em>per-point annotations</em> of the categories of the objects and rooms appearing in the reconstructed scenarios, and <em>per-pixel annotations</em> of each RGB-D image within the recorded sequences</li> </ul> <p>During the data collection, a total of 36 rooms were completely inspected, so the dataset is rich in contextual information of objects and rooms. This is a valuable feature, missing in most of the state-of-the-art datasets, which can be exploited by, for instance, semantic mapping systems that leverage relationships like <em>pillows are usually on beds</em> or <em>ovens are not in bathrooms</em>.</p> <p><strong>Robot@Home2</strong></p> <p><a href="https://github.com/goyoambrosio/RobotAtHome2">Robot@Home2</a>, is an enhanced version aimed at improving usability and functionality for developing and testing mobile robotics and computer vision algorithms. It consists of three main components. Firstly, a <a href="#bottom"><strong>relational database</strong></a> that states the contextual information and data links, compatible with Standard Query Language. Secondly,a <a href="https://pypi.org/project/robotathome/"><strong>Python package</strong></a> for managing the database, including downloading, querying, and interfacing functions. Finally, learning resources in the form of <a href="https://drive.google.com/drive/folders/1ENnxbKP5MJdlGl2Q93WTbIlofuy6Icxq"><strong>Jupyter notebooks</strong></a>, runnable locally or on the Google Colab platform, enabling users to explore the dataset without local installations. These freely available tools are expected to enhance the ease of exploiting the Robot@Home dataset and accelerate research in computer vision and robotics.</p> <p>If you use Robot@Home2, please cite the following <a href="https://www.sciencedirect.com/science/article/pii/S2352711023001863">paper</a>:</p> <p>Gregorio Ambrosio-Cestero, Jose-Raul Ruiz-Sarmiento, Javier Gonzalez-Jimenez, <strong>The Robot@Home2 dataset: A new release with improved usability tools</strong>, in <em>SoftwareX, Volume 23, 2023, 101490, ISSN 2352-7110</em>, <a href="https://doi.org/10.1016/j.softx.2023.101490">https://doi.org/10.1016/j.softx.2023.101490</a>.</p> <blockquote>@article{ambrosio2023robotathome2,<br>title = {The Robot@Home2 dataset: A new release with improved usability tools},<br>author = {Gregorio Ambrosio-Cestero and Jose-Raul Ruiz-Sarmiento and Javier Gonzalez-Jimenez},<br>journal = {SoftwareX},<br>volume = {23},<br>pages = {101490},<br>year = {2023},<br>issn = {2352-7110},<br>doi = {https://doi.org/10.1016/j.softx.2023.101490},<br>url = {https://www.sciencedirect.com/science/article/pii/S2352711023001863},<br>keywords = {Dataset, Mobile robotics, Relational database, Python, Jupyter, Google Colab}<br>}<br> </blockquote> <p><strong>Version history</strong><br><a href="../record/3901564">v1.0.1</a> Fixed minor bugs.<br><a href="../record/4495821">v1.0.2</a> Fixed some inconsistencies in some directory names. Fixes were necessary to automate the generation of the next version.<br><a href="../record/4499043">v2.0.0</a> SQL based dataset. Robot@Home v1.0.2 has been packed into a <a href="https://www.sqlite.org/index.html">sqlite</a> database along with RGB-D and scene files which have been assembled into a hierarchical structured directory free of redundancies. Path tables are also provided to reference files in both v1.0.2 and v2.0.0 directory hierarchies. This version has been automatically generated from version 1.0.2 through the <a href="https://github.com/goyoambrosio/RobotAtHome2">toolbox</a>.<br><a href="../record/4530453">v2.0.1</a> A forgotten foreign key pair have been added.<br><a href="../records/7811783">v.2.0.2</a> The views have been consolidated as tables which allows a considerable improvement in access time.<br><a href="../records/7811795">v.2.0.3</a> The previous version does not include the database. In this version the database has been uploaded.<br>v.2.1.0 Depth images have been updated to 16-bit. Additionally, both the RGB images and the depth images are oriented in the original camera format, i.e. landscape.</p>
Dataset of "Social Robots and Sensors for Enhanced Ageing at Home: A Focus on Mobility and Socioeconomic Factors."
<p>This dataset supports the article:</p> <p>"Social Robots and Sensors for Enhanced Aging at Home: A Focus on Mobility and Socioeconomic Factors."</p> <p>For further details see the Readme.txt file.</p>
Real-world human-robot interaction data with robotic pets in user homes in the United States and South Korea
<p>Socially-assistive robots (SARs) hold significant potential to transform the management of chronic healthcare conditions (e.g. diabetes, Alzheimer's, dementia) outside the clinic walls. However doing so entails embedding such autonomous robots into people's daily lives and home living environments, which are deeply shaped by the cultural and geographic locations within which they are situated. That begs the question of whether we can design autonomous interactive behaviors between SARs and humans based on universal machine learning (ML) and deep learning (DL) models of robotic sensor data that would work across such diverse environments. To investigate this, we conducted a long-term user study with 26 participants across two diverse locations (the United States and South Korea) with SARs deployed in each user's home for several weeks. We collected robotic sensor data every second of every day, combined with sophisticated ecological momentary assessment (EMA) sampling techniques, to generate a large-scale dataset of over 270 million data points representing 173 hours of randomly-sampled naturalistic interaction data between the human and robot pet. Interaction behaviors included activities like playing, petting, talking, cooking, etc.</p>
Data from: Social robots as conversational catalysts: Enhancing long-term human-human dyadic interaction at home
Open the record for dataset details and reuse information.
Real-world human-robot interaction data with robotic pets in user homes in the United States and South Korea
Open the record for dataset details and reuse information.
Bilateral Stand-alone Robotic Motion-Assisted Finger Exoskeleton for Home Rehabilitation
<p><span>This presents a novel exoskeleton robot which can be used at home for rehabilitating the index fingers of stroke-affected patients. This exoskeleton is designed as a one degree-of-freedom four bar mechanism able to guide the human index finger motion. The proposed device is the only lateral, stand-alone mechanism built till date which can carry the weight of the human hand, thus making the user free from wearing it. The design starts by tracing the trajectory of the index finger using ‘Angulus’ software. ‘SALAR’ software is used for dimensional synthesis of four bar mechanism. Using additive manufacturing technology, a prototype of the proposed device is developed. Static force analysis is done to select the most appropriate actuator for producing the required torque to manipulate the fingers effectively. The kinematics of the index finger while performing finger curl exercise is obtained. The proposed linkage mechanism can drive the index fingers of both the hands. Simulation and experimental results proved feasibility and effectiveness of the proposed design to be used for index finger rehabilitation for a wide range of users and applications by making simple minor alterations in the design. Also, the device can be used for rehabilitating the middle fingers together with the index fingers.</span></p>
Clinic to Home Robotics-assisted Telerehabilitation for Upper Limb (CHISEL)
ClinicalTrials.gov study NCT05212181. IPD Sharing: NO. Countries: 1. Publications: 1.
The Presence of Humanoid Robot With Older Adults at Homes
ClinicalTrials.gov study NCT06487611. IPD Sharing: NO. Countries: 1. Publications: 1.
Exploring Use of Companion Robot Pets for Older Adults in Care Homes
ClinicalTrials.gov study NCT04168463. IPD Sharing: NO. Countries: 1. Publications: 3.
Experience With a Robot for Home Care and Its Acceptance by People With Dementia, Caregivers and Dementia Trainers
ClinicalTrials.gov study NCT03823066. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Study of the Impact of a Social Telepresence Robot on Social Isolation and Loneliness of the Elderly at Home
ClinicalTrials.gov study NCT04767100. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effectiveness and Safety of At-home Gait Rehabilitation Using Wearable Exoskeletal Robot
ClinicalTrials.gov study NCT06543758. IPD Sharing: NO. Countries: 1. Publications: 22.
Assessment of the Acceptability of a Humanoid Robot at Home for Children With Cochlear Implants - H2R2
ClinicalTrials.gov study NCT04832373. IPD Sharing: NO. Countries: 1. Publications: 2.
A Smart Home-based Exoskeleton Robot System for Stroke Patients
ClinicalTrials.gov study NCT04463888. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effects of a Robot on Physical and Psychosocial Outcomes of Persons With Dementia and Their Social Environment at Home
ClinicalTrials.gov study NCT03818217. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
Use of a Robot in Medication Management for Older People's Home Care
ClinicalTrials.gov study NCT05908604. IPD Sharing: NO. Countries: 1. Publications: 1.
Assessment of Educational Effect of Home-made Robotic Surgery Simulator for Novice Robotic Surgeons
ClinicalTrials.gov study NCT03067532. IPD Sharing: NO. Countries: 1. Publications: 0.
Robot for Alleviating Loneliness and Engaging Nursing Home Residents
ClinicalTrials.gov study NCT06174337. IPD Sharing: NO. Countries: 1. Publications: 0.
Study of the Impact of a Social Robot on Unwanted Loneliness in Elderly People Living in Nursing Homes
ClinicalTrials.gov study NCT06344676. IPD Sharing: NO. Countries: 0. Publications: 0.
Dataset related to article "Early Hospital Discharge on Day Two Post Robotic Lobectomy with Telehealth Home Monitoring: A Pilot Study"
<p>This record contains raw data related to article "Early Hospital Discharge on Day Two Post Robotic Lobectomy with Telehealth Home Monitoring: A Pilot Study"</p><p><strong> Abstract</strong></p><p>Despite the adoption of enhanced recovery programs, the reported postoperative length of stay after robotic surgery is 4 days even in highly specialized centers. We report preliminary results of a pilot study for a new protocol of early discharge (on day 2) with telehealth home monitoring after robotic lobectomy for lung cancer. All patients with a caregiver were discharged on postoperative day 2 with a telemonitoring device if they satisfied specific discharge criteria. Teleconsultations were scheduled once in the afternoon of post-operative day 2, twice on postoperative day 3, and then once a day until the chest tube removal. Post-discharge vital signs were recorded by patients at least four times daily through the device and were available for consultation by two surgeons through phone application. In case of sudden variation of vital signs or occurrence of adverse events, a direct telephone line was available for patients as well as a protected re-hospitalization path. Primary outcome was the safety evaluated by the occurrence of post-discharge complications and readmissions. Secondary outcome was the evaluation of resources optimization (hospitalization days) maintaining the standard of care. During the study period, twelve patients satisfied all preoperative clinical criteria to be enrolled in our protocol. Two of twelve enrolled patients were successively excluded because they did not satisfy discharge criteria on postoperative day 2. During telehealth home monitoring a total of 27/427 vital-sign measurements violated the threshold in seven patients. Among the threshold violations, only 1 out of 27 was a critical violation and was managed at home. No postoperative complication occurred neither readmission was needed. A mean number of three hospitalization days was avoided and an estimated economic benefit of about EUR 500 for a single patient was obtained if compared with patients submitted to VATS lobectomy in the same period. These preliminary results confirm that adoption of telemonitoring allows, in selected patients, a safe discharge on postoperative day 2 after robotic surgery for early-stage NSCLC. A potential economic benefit could derive from this protocol if this data will be confirmed in larger sample.</p><p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.