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2,639 results for “Robotic”
Data from: Color pattern facilitates species recognition but not signal detection: a field test using robots
There are many factors that affect signal design, including the need for rapid signal detection and the ability to identify the signal as conspecific. Understanding these different sources of selection on signal design is essential to explain the evolution of both signal complexity and signal diversity. We assessed the relative importance of detection and recognition for signal design in the black-bearded gliding lizard, Draco melanopogon, which uses the extension and retraction of a large, black-and-white dewlap (or throat fan) in territorial communication. We presented free-living lizards with robots displaying dewlaps of different designs that varied in the proportion of the black and white components. We found no effect of dewlap brightness or design on the time it took for a lizard to detect the robot, consistent with the view that initial detection is likely to be primarily elicited by movement rather than specific color or pattern. However, males (but not females) responded with a greater intensity to the dewlap treatment that most resembled the natural dewlap color and design of the species. Furthermore, males were more likely to display to any dewlap color in the presence of a neighbor. These results suggest that dewlap pattern may play an important role in species recognition but has minimal influence on the initial detection of the signal. Importantly, our results also highlight that factors unrelated to discrimination, such as social cues and individual motivational state, may affect responses to species identity cues.
Data from: Using a robotic fish to investigate individual differences in social responsiveness in the guppy
Responding towards the actions of others is one of the most important behavioral traits whenever animals of the same species interact. Mutual influences among interacting individuals may modulate the social responsiveness seen and thus makes it often difficult to study the level and individual variation in responsiveness. Here, open-loop biomimetic robots that provide standardized, non-interactive social cues can be a useful tool. These robots are not affected by the live animal's actions but are assumed to still represent valuable and biologically relevant social cues. As this assumption is crucial for the use of biomimetic robots in behavioral studies, we hypothesized (a) that meaningful social interactions can be assumed if live animals maintain individual differences in responsiveness both when interacting with a biomimetic robot and a live partner. Furthermore, to study the level of individual variation in social responsiveness, we hypothesized (b) that individual differences should be maintained over the course of multiple tests with the robot. We investigated the response of live guppies (Poecilia reticulata) when allowed to interact either with a biomimetic open-loop controlled fish robot – 'Robofish' – or a live companion. Furthermore we investigated the responses of live guppies when tested three times with Robofish. We found that live guppies' responses towards Robofish were weaker compared to a live companion, most likely as a result of the non-interactive open-loop behavior of Robofish. Guppies, however, were consistent in their individual responses between a live companion and Robofish and similar individual differences in response towards Robofish were maintained over repeated testing even though habituation to the test environment was detectable. Biomimetic robots like Robofish are therefore a useful tool for the study of social responsiveness in guppies and possibly other small fish species.
Data from: Unshackling evolution: evolving soft robots with multiple materials and a powerful generative encoding
In 1994 Karl Sims showed that computational evolution can produce interesting morphologies that resemble natural organisms. Despite nearly two decades of work since, evolved morphologies are not obviously more complex or natural, and the field seems to have hit a complexity ceiling. One hypothesis for the lack of increased complexity is that most work, including Sims', evolves morphologies composed of rigid elements, such as solid cubes and cylinders, limiting the design space. A second hypothesis is that the encodings of previous work have been overly regular, not allowing complex regularities with variation. Here we test both hypotheses by evolving soft robots with multiple materials and a powerful generative encoding called a compositional pattern-producing network (CPPN). Robots are selected for locomotion speed. We find that CPPNs evolve faster robots than a direct encoding and that the CPPN morphologies appear more natural. We also find that locomotion performance increases as more materials are added, that diversity of form and behavior can be increased with different cost functions without stifling performance, and that organisms can be evolved at different levels of resolution. These findings suggest the ability of generative soft-voxel systems to scale towards evolving a large diversity of complex, natural, multi-material creatures. Our results suggest that future work that combines the evolution of CPPN-encoded soft, multi-material robots with modern diversity-encouraging techniques could finally enable the creation of creatures far more complex and interesting than those produced by Sims nearly twenty years ago.
Braiding Thymios (robots view)
<p>Braiding thymios (robots view)</p>
Dataset for AI Co-pilot Bronchoscope Robot
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Human motor augmentation via an extra-robotic arm without functional interference
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Acoustic Monitoring Dataset for Robotic Laser Directed Energy Deposition (LDED) of Maraging Steel C300
<p>This dataset presents a set of acoustic signals captured during a single-bead wall experiment in robotic Laser Directed Energy Deposition (LDED) using Maraging Steel C300. The acoustic data was recorded using a high-fidelity Prepolarized microphone sensor (Xiris WeldMIC), capturing the intricate sound profiles associated with the LDED process at a sampling rate of 44,100 Hz.</p><p><strong>Laser Directed Energy Deposition:</strong></p><p>This dataset was generated with a robotic LDED process that consists of a six-axis industrial robot (KUKA KR90) coupled with a two-axis positioner, a laser head, and a coaxial powder-feeding nozzle.</p><p> </p><p><strong>Folder Structure:</strong></p><ul><li><strong>/sample-1</strong>: The main folder for the experiment sample.<ul><li><strong>/audio_files</strong>: Contains 4624 <strong>.wav</strong> audio files, each representing a 40 ms chunk of the LDED process sound.</li><li><strong>/annotations_1.csv</strong>: A CSV file providing annotations for the audio files, labeling each as "Defect-free", "Defective", or "Laser-off".</li></ul></li><li>audio_features.h5: extracted acoustic features in time-domain, frequency-domain, and time-frequency representations (MFCC features). Feature extraction was conducted using Python Essentia Library.</li></ul><p> </p><p><strong>File Naming Convention:</strong></p><ul><li>Audio files within the <strong>audio_files</strong> folder are named following the pattern <strong>sample_ExperimentID_SampleID.wav</strong>. Given that there's only one experiment and one sample, the naming will be consistent, for example, <strong>sample_1_1.wav</strong> for the first file.</li></ul><p><strong>Annotation Details:</strong></p><ul><li>The <strong>annotations_1.csv</strong> file contains detailed labels for each audio file, correlating to the conditions observed during the experiment, aiding in quick identification and analysis.</li></ul><p><strong>Experimental Parameters:</strong> The dataset reflects a controlled experiment setup with the following specifications:</p><ul><li>Geometry: Single bead wall structure</li><li>Dimensions: 90 mm * 42.5 mm</li><li>Number of layers: 50</li><li>Laser beam diameter: 2 mm</li><li>Layer thickness: 0.85 mm</li><li>Stand-off distance: 12 mm</li><li>Laser profile: Gaussian</li><li>Laser wavelength: 1064 nm</li></ul><p><strong>Process Parameters:</strong></p><ul><li>Laser power: 2.3 kW</li><li>Speed: 25 mm/s</li><li>Dwell time: 0 s</li><li>Powder flow rate: 12 g/min</li></ul><p>This dataset aims to facilitate the development and testing of acoustic-based defect detection models for real-time quality monitoring in LDED processes. It can also serve as a reference point for further research on sensor fusion, machine learning, and real-time monitoring of manufacturing processes.</p>
Bioinspired Design and Experimental Validation of an Aquatic Snake Robot
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Participatory Design Materials: Co-designing Child-Robot Relational Norm Intervention to Regulate Children's Handwriting Posture
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Appendix_Data_Industrial application of Multi-Robot Partial Destructive Disassembly Line Balancing for Multi-Product Scenarios_v1.docx
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Data set and simulation code for "Design and Control Optimization for Hybrid-Controlled Overconstrained Cable-Driven Parallel Robots"
<p>See the attached readme file</p>
Cirq Robotic Module assisted pedicle screw Implantation - Operative video
<p>Cirq Robotic Module assisted pedicle screw Implantation - Operative video</p>
Beyond motor recovery after stroke: The role of hand robotic rehabilitation plus virtual reality in improving cognitive function
<p>Robot-assisted hand training adopting end-effector devices results in an additional reduction of motor impairment in comparison to usual care alone in different stages of stroke recovery. These devices often allow the patient to perform practical, attentive, and visual-spatial tasks in a semi-virtual reality (VR) setting. We aimed to investigate whether the hand end-effector robotic device Amadeo<sup>TM</sup> could improve cognitive performance, beyond the motor deficit, as compared to the same amount of occupational treatment focused on the hand. Forty-eight patients (aged 54.3 ± 10.5 years, 62.5% female) affected by either ischemic or hemorrhagic stroke in the chronic phase were enrolled in the study. The experimental group (EG) underwent Amadeo<sup>TM</sup> robotic training, while the control group (CG) performed occupational therapy involving the upper limb. Patients were assessed at the beginning and at the end of the rehabilitation protocol using a specific neuropsychological battery, as well as motor function tests. The EG showed greater improvements in different cognitive domains, including attentive abilities and executive functions, as well as in hand motor function, as compared to CG. Our study showed that task-oriented VR-based robotic rehabilitation enhanced not only motor function in the paretic arm but also global and specific cognitive abilities in post-stroke patients. We may argue that the hand robotic plus VR-based training may provide patients with an integration of cognitive and motor skill rehabilitation, thus amplifying the functional outcome achievement.</p>
Data acquired by Modular-E robot in Quinta do Seixo on 07-07-2022
<p>Data acquired by Modular-E robot in Quinta do Seixo on 07-07-2022</p>
Demos of attacks against industrial robots
<p>Demos of attacks against industrial robots.</p>
Supplementary material 1 from: Smith C, Todd M, Patiny L, Swain C, Southan C, Williamson A, Clark A (2016) SCINDR - The SCience INtroDuction Robot that will Connect Open Scientists. Research Ideas and Outcomes 2: e9995. https://doi.org/10.3897/rio.2.e9995
SCINDR Open Science Prize Proposal
Figure 1 from: Smith C, Todd M, Patiny L, Swain C, Southan C, Williamson A, Clark A (2016) SCINDR - The SCience INtroDuction Robot that will Connect Open Scientists. Research Ideas and Outcomes 2: e9995. https://doi.org/10.3897/rio.2.e9995
Figure 1 - SCINDR, the Science Introduction Robot, watches health research being carried out and, like a good host, introduces people with shared interests, so they can do better work together.
Figure 2 from: Smith C, Todd M, Patiny L, Swain C, Southan C, Williamson A, Clark A (2016) SCINDR - The SCience INtroDuction Robot that will Connect Open Scientists. Research Ideas and Outcomes 2: e9995. https://doi.org/10.3897/rio.2.e9995
Figure 2 - Example of currently functioning Electronic Laboratory Notebook (ELN) entry to which SCINDR will be added. Further enhancements such as real time NMR, LCMS and IR data visualization have been developed and will be added to extend the ELN capability.
A Geometric Pulling Force Controller for Aerial Robotic Workers
<p> This video presents a geometric, pulling force control scheme in order to enable the concept of Aerial Robotic Workers (ARWs), where the capabilities of the Unmanned Aerial Vehicles (UAVs) are enhanced by aerial manipulators in order to exert known pulling forces on the environment, with characteristic applications such as levers actuation, debris removal and safety assessments. The proposed novel approach consists of interfacing a cascaded position control scheme with a manipulation framework in such a way that the UAV, together with the manipulator are being controlled in a complete system.</p>
Supplementary Material: Emergent Orchestras: A Modular Framework for Musical Robot Swarms
<p>Supplementary Material containing the experiments described in the article.</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)
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.