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6 results for “Rule Based System”
Figure 4. (a)Our Humanoid soccer robot, (b) Overview of the Control System-Design and Implementation of an Autonomous Humanoid Robot Based on Fuzzy Rule-Based Motion Controller
<p>Figure 4 shows the block diagram of the software which runs in the robot’s main processor.<br> The program consists of 4 main blocks:<br> • Hardware Interface: Contains all low level routines to access hardware of the robot including<br> sensors and actuators.<br> • Vision: Contains image processing algorithms such as recognition of landmarks and other<br> object. Self localization is done using particle filtering. Particles are scored by comparing a<br> simulated image from each particle with the current frame captured by camera. Using<br> “Sampling-Importance Resampling” method, a new distribution of the particles is created after<br> each step.<br> Particles are also updated using a motion model. Final distribution of the particles converges to<br> the real pose of the robot.<br> • Planning: Planning system of the robot is based on a multi layer, and multi thread structure.<br> The layers are named Strategy, Role, Behavior and Motion. Each layer contains a Scenario<br> which runs in parallel with the scenarios in the other layers. A scenario in a higher level can<br> terminate and change the scenario running in the lower level; however it is usually done in<br> synchronization with the lower level scenario to avoid conflicts and instabilities. (Such as<br> stopping the walking motion while one of the feet is still in the air).<br> • Network: Mainly responsible for the wireless communication of the robot with the other robots<br> or the referee box. This is done via WLAN.<br> • Motion Control: manages all the actuators of the robot, and controls locomotion or any other<br> action of the robot according to the requests from Cognition.<br> • Sensor Control: manages other sensors, and interacts with the Sub-Controller.</p>
Figure 3. (a) Our Humanoid soccer robot, (b) Overview of the Control System-Design and Implementation of an Autonomous Humanoid Robot Based on Fuzzy Rule-Based Motion Controller
<p>The PERSIA Humanoid robot designed for has multipurpose capability. This robot<br> equipped with main board for motion control, vision sensor, other balancing sensors, servo motors<br> and etc. Figure 3 shows picture of the robot and overview of the Persia humanoid robot control<br> system.</p>
BRAIN Journal-Right-Linear Languages Generated in Systems of Knowledge Representation based on LSG-Right-Figure 2. The representation of the rule
<p>In order to model these derivations in the stratified graph G, each production of the grammar will be represented in the labeled graph G0 by a direct arc of the form given in Figure 2.</p> <p> </p>
A tectonic-rules-based mantle reference frame since 1 billion years ago – implications for supercontinent cycles and plate–mantle system evolution
<p>The archive <strong>Muller_etal_2022_SE_1Ga_Opt_PlateMotionModel.zip</strong> contains the files for the plate model in an optimised mantle reference frame. GPlates or pyGPlates software (<a href="https://www.gplates.org/">www.gplates.org</a>) is needed to read these files. </p> <p>The archive <strong>Muller_etal_2022_SE_mantle-ref-frame-oceanic-crustal-agegrids.zip</strong> contains the oceanic crustal age grids in netCDF-4 format for the optimised mantle reference frame plate model, while the archive <strong>Muller_etal_2022_SE_PMAG_oceanic-crustal-agegrids.zip</strong> contains the oceanic crustal age grids in netCDF-4 format for the paleomagnetic reference frame plate model from Merdith et al. (2021).</p> <p> </p> <p>The agegrids associated with this model can be accessed at: <a href="https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2022_SE/" target="_blank" rel="noopener">https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2022_SE/</a></p>
Rule-Based Closed Loop System for Type 1 Diabetes Control
ClinicalTrials.gov study NCT01614496. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: General rules for environmental management to prioritise social-ecological systems research based on a value of information approach
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.