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2,639 results for “Robotic”
Synthetic Multimodal Dataset using ABB Studio: Dual Robot Welding Station
<p>## README</p> <p>### Overview</p> <p>This repository provides the setup and data collected from simulations conducted in RobotStudio for various ABB robot configurations. The simulation, based on Diprasetya et al. (2023), was designed to capture precise sensory data in a controlled environment that mirrors real-world welding conditions.</p> <p>### Simulation Setup</p> <p>The simulation tracks essential parameters of the ABB robot and its end-effector, including:<br>- **Joint Angles**: Real-time angles for each joint.<br>- **TCP Position**: 3D positional coordinates of the Tool Center Point.<br>- **TCP Orientation**: Orientation captured as quaternions to represent rotational states.<br>- **Additional Attributes**: Various other robot-specific details relevant to performance in a welding setup.</p> <p>### Data Collection</p> <p>To generate a high-resolution dataset, data were sampled at intervals between 12 ms and 96 ms. This detailed sampling provides accurate insights into the robot's operation in a simulated welding environment.</p> <p>### Key Parameters</p> <p>The dataset includes the following parameters for each robot:</p> <p>- **Camera View**: One camera view with a resolution of 3 x 256 x 256, normalized to the range [0, 1].<br>- **Motor Power (P)**: The power consumed by the robot’s motors, constrained within \([0, P_{\text{max}}]\).<br>- **TCP Speed (v_TCP)**: The velocity of the end-effector, with a maximum cap of 5 m/s.<br>- **TCP Acceleration (a_TCP)**: The acceleration of the TCP, bounded within \([a_{\text{min}}, a_{\text{max}}]\).<br>- **TCP Orientation (q_TCP)**: Quaternion representing orientation, with a normalization condition \(||\mathbf{q}_{\text{TCP}}(t)|| = 1\).<br>- **TCP Position (p_TCP)**: A 3D vector for positional coordinates, with each coordinate constrained within \([p_{\text{min}}, p_{\text{max}}]\).<br>- **Braking Distance (d_brake)**: The distance each joint travels during braking, within bounds \([d_{\text{min}}, d_{\text{max}}]\).<br>- **Holding Position (θ_hold)**: The maintained angles for each joint, constrained to the interval \([-π, π]\).<br>- **Joint Angles (θ)**: The current angles of each joint, also within the interval \([-π, π]\).</p> <p><br>### Citation</p> <p>For more details on the simulation methodology, please refer to:<br>- Diprasetya, M. R., Yuwono, S., Löppenberg, M., & Schwung, A. (2023, July). Integration of ABB Robot Manipulators and Robot Operating System for Industrial Automation. In 2023 IEEE 21st International Conference on Industrial Informatics (INDIN) (pp. 1-7). IEEE.</p>
Data set and simulation code for "Static workspace computation for underactuated cable-driven parallel robots"
<p>See the attached readme file</p>
Data from: Mate choice and the operational sex ratio: an experimental test with robotic crabs
The operational sex ratio (OSR) (sexually active males: receptive females) predicts the intensity of competition for mates. It is less clear, however, under what circumstances the OSR predicts the strength of sexual selection – that is, the extent to which variation in mating success is attributable to traits that increase the bearer's attractiveness and/or fighting ability. To establish causality experiments are required that manipulate OSR. Furthermore, if it is possible to control for any OSR-dependent changes in the chosen sex (e.g. changes in male courtship), we can directly test whether the OSR affects the behaviour of the choosing sex (e.g. female choice decisions). We conducted female mate choice experiments in the field using robotic models of male fiddler crabs (Uca mjoebergi). We used a novel design with two females tested sequentially per trial. As in nature, the choice of the first female to mate therefore affected the mates available to the next female. In general we detected significant sexual selection due to female choice for 'males' with larger claws. Importantly, the strength of sexual selection did not vary across five different OSR/density treatments. However, as the OSR decreased (hence the number of available males declined), females chose the 'males' with the largest claws available significantly more often than expected by chance. Possible reasons for this mismatch between the expected and observed effects of the OSR on the strength of sexual selection are discussed.
Data from: Testing the limits of pheromone stigmergy in spatially constrained robotic swarms
Area coverage and collective exploration are key challenges for swarm robotics. Previous research in this field has drawn inspiration from ant colonies, with real, or more commonly virtual, pheromones deposited into a shared environment to coordinate behaviour through stigmergy. Repellent pheromones can facilitate rapid dispersal of robotic agents, yet this has been demonstrated only for relatively small swarm sizes (N<30). Here, we report findings from swarms of real robots (Kilobots) an order of magnitude larger (N>300), and from realistic simulation experiments up to N=400. We identify limitations to stigmergy in a spatially constrained environment – a free but bounded two-dimensional workspace – using repellent binary pheromone. At larger N a simple, stigmergic avoidance algorithm becomes first no better, then inferior to, the area coverage of non-interacting random walkers. Thus, with ever-increasing swarm sizes, the assumption of robustness and scalability for such approaches may need to be re-examined. Instead, subcellular biology, and diffusive processes, may prove a better source of inspiration at large N in spatially constrained or high agent density environments.
Data from: Noninvasive neuroimaging enhances continuous neural tracking for robotic device control
Brain-computer interfaces (BCIs) using signals acquired with intracortical implants have achieved successful high-dimensional robotic device control useful for completing daily tasks. However, the substantial amount of medical and surgical expertise required to correctly implant and operate these systems greatly limits their use beyond a few clinical cases. A noninvasive counterpart requiring less intervention that can provide high-quality control would profoundly improve the integration of BCIs into the clinical and home setting. Here, we present and validate a noninvasive framework using electroencephalography (EEG) to achieve the neural control of a robotic device for continuous random target tracking. This framework addresses and improves upon both the "brain" and "computer" components by increasing, respectively, user engagement through a continuous pursuit task and associated training paradigm and the spatial resolution of noninvasive neural data through EEG source imaging. In all, our unique framework enhanced BCI learning by nearly 60% for traditional center-out tasks and by more than 500% in the more realistic continuous pursuit task. We further demonstrated an additional enhancement in BCI control of almost 10% by using online noninvasive neuroimaging. Last, this framework was deployed in a physical task, demonstrating a near-seamless transition from the control of an unconstrained virtual cursor to the real-time control of a robotic arm. Such combined advances in the quality of neural decoding and the practical utility of noninvasive robotic arm control will have major implications for the eventual development and implementation of neurorobotics by means of noninvasive BCI.
Dataset for Robot-mounted digital 3D-microscope versus standard microscope for spinal decompression surgery
<p>Compilation of all data collected in the study.</p> <p>- Depth Perception Robotc: Data collected during depth perception experiments with the BHS RoboticScope</p> <p>- Depth Perception Cons: Data collected during depth perception experiments with the OM</p> <p>- Both Scopes Combined: Combined data regarding depth perception experiments</p> <p>- Questionaire Combined: Combined data regarding cadaveric experiments</p> <p>- Questionaire expsurg1: completed questionnaire by the experienced surgeon 1</p> <p>- Questionaire expsurg3: completed questionnaire by the experienced surgeon 3</p>
Three device parenchyma dissection in robotic surgery
<p>We present a novel technique for the transection liver parenchyma during robotic surgery, using three devices (3D) simultaneously: monopolar scissors and bipolar Maryland forceps of the robot and laparoscopic-guided waterjet.</p>
A Robotic Platform for Synthesis of Colloidal Nanocrystals
<p>Code, algorithm, and data are available to generate results that are reported in the paper and central to the main claims.</p> <p>1. Code and README for data mining of synthesis parameters.</p> <p>2. Code for reading in situ color characterization results.</p> <p>3. Code, README and figure drawing (an example) of ML prediction by SISSO.</p> <p> </p>
Towards a simultaneously speaking bilingual robot: Primary study on the effect of gender and pitch of the robot's voice
<p>With fast and reliable international transportation, more people with different language backgrounds can interact now. As a result, the need for communicative agents fluent in several languages to assist those people is highlighted. The high cost of hiring human attendants fluent in several languages makes using social robots a more affordable alternative in international gatherings. A social robot capable of presenting a piece of information in more than one language at the same time to its audience is the goal of this line of study. However, the negative effect of background noise on speech comprehension in humans is well-established. Hence, presenting a piece of information in two different languages at the same time by the robot creates an adverse listening condition for both individuals listening to the speech of such a bilingual robot. In this study, we investigated whether manipulating the pitch and gender of the robot's voice could affect human subjects' memory of the presented information in the presence of background noise. The results indicate that the pitch and gender of the speaking voice do indeed affect our memory of the presented information. when a male voice was used, a higher pitch resulted in significantly better memory performance than a lower pitch. Contrarily, when a female voice was used, a lower pitch resulted in significantly better memory in participants than a higher pitch. Both male and female subjects performed significantly better with a female voice in a noisy background. In nutshell, the result of this study suggests using a female voice for robots in noisy conditions, as in the case of simultaneously speaking robots, can significantly improve the retrieval of presented information in human subjects.</p>
Files for: Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling
<p>This repository includes the files necessary to reproduce the digital anatomies, cardiac and aortic sleeves, and multi-material 3D-printed valves from the "Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling" article.</p>
(Embodied) Artificial Intelligence: making robots curious
<p><strong>The following video describes how, active vision and embodied artificial inteligence contribute to the ROMI platform. Funded by EU Grant 773875.</strong></p> <p><em>Videos are available in:</em></p> <ul> <li>Hi-res (1080p Apple ProRes)</li> <li>Mid-res (1080p H265)</li> </ul> <p><strong>Video script:</strong></p> <p>(MINCHIN) At Humboldt University we see how ‘embodied artificial intelligence’, ‘computer vision’ and ‘active vision’, have been used to create feedbacks between an environment and the robotic tools in motion.<br> <br> (HAFNER) Our big goal is to understand intelligence, and to understand the principles of intelligence in natural systems like humans and other animals, and to extract these principles and put them into algorithms and put and test them in robots. We think that not everything can be pre-programmed into the robot, but the robot has to learn and make experiences by the interaction of the real world. So I can show that here, so the robot is like a child randomly moving its arm around, and at the same time learning the correlation between the motor commands here and the position of the hand as the robot can see, by its own, by its own camera. That that approach is called ‘embodied artificial intelligence’ this adaptive approach is very much important for the ROMI project where we're partners in, because we can't program everything just by hand because the the conditions change you have difference, you don't know how the how the area looks like the maybe even the robot hardware changes, the motor changes and so we can use our adaptive methods and apply them to the ROMI robots so that they can really interact with the with the plants and extract information from the plants.<br> <br> (SCHILLACI) We have a system that implements a sort of artificial curiosity. The artificial curiosity drives the movement of the robot towards interesting locations. For instance one of our tasks is to support the 3d reconstruction of plants, and instead of using predefined movements of the 3d scanner around the plants, our system instead is trying to to make more intelligent movements to to discover parts of the object that perhaps are more interesting to look at.<br> <br> So we have the learning system running at the moment, so we have the artificial curiosity explorer based exploration that sends motor commands and at the same time this, so all the information that are recorded from from the robot which are images which you can see here, and the positions of the robot are sent to the model which is going to be trained. So you probably have a goal that is like; look at the tracks, like put the tripod at the centre of the image so that's probably one of the goal. And the idea is that the next step will be like to have to move around this goal so as soon as your system is well trained, so this goal could be could be changing, for instance because the plant is growing, so you need to to move these goals around to make the system adaptive. Tt's coming back again to the tripod this one.<br> <br> (HAFNER)<strong> </strong>In ROMI it's a very challenging task because we have to we have to cope with this these real systems and we have to cope with with wind and with weather and the plants growing unexpectedly and so it's very challenging, but it's also very fascinating.<br> <br> (SCHILLACI)<strong> </strong>So the next step will be having more movement capabilities, so you will be able to segment out parts of the images that you don't need. Antonio is actually working on segmenting out the interesting objects from the from the scene, and in particular also to avoid the arm to crash into plants. So you you take first a screenshot from from a camera that is located at the top of the robot and then so you segment out all the objects that you don't need, and the object also where the robot could crash so you your trajectories will be going around plans do not crash onto them.</p>
Sunlight-powered self-excited oscillators for sustainable autonomous soft robotics
<p>As soft robotics fast advances, full autonomy becomes highly sought, especially if their motion can be powered by environmental energy and self-regulated. This would present a self-sustained fashion in terms of both energy supply and motion control. Currently, autonomous movement can be realized by leveraging out-of-equilibrium oscillatory motion of stimuli-responsive polymers under a constant light source. It would be more advantageous if environmental energy can be scavenged to power robots. However, generating oscillation becomes challenging under the limited power density of available environmental energy sources. Herein, we develop fully autonomous soft robots with self-sustainability based on self-oscillation. Aided by multiphysics modeling, we have successfully reduced the required input power density to around one-Sun level through a liquid crystal elastomer (LCE)-based bilayer structure. The autonomous motion of the low-intensity LCE/elastomer bilayer oscillator “LiLBot” under low energy supply was achieved by high photothermal conversion, low modulus, and high material responsiveness simultaneously. The LiLBot features tunable peak-to-peak amplitudes from 4 degrees to 72 degrees and frequencies from 0.3 Hertz to 11 Hertz. The oscillation approach offers a general strategy for desgining autonomous, untethered and sustainable small-scale soft robots, such as sailboat, walker, roller, and synchronized flapping wings.</p>
A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots
<p>This dataset is a part of the supplementary materials to the 2017 RAL <a href="https://ieeexplore.ieee.org/document/7358076">article</a> with the same title.</p> <blockquote> <p>A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots</p> <p>IEEE Robotics and Automation Letters</p> <p>Alessandro Giusti, Jerome Guzzi, Dan Ciresan, Fang Lin He, Juan Pablo Rodriguez, Flavio Fontana, Matthias Faessler, Christian Forster, Jurgen Schmidhuber, Gianni A. Di Caro, Davide Scaramuzza, Luca Gambardella</p> </blockquote> <p>You can find more information on the <a href="http://bit.ly/perceivingtrails">project web page</a> (alessandrog@idsia.ch).</p> <p><strong>Dataset</strong></p> <p>Folders 001..010 contain the dataset used to train the networks. Folder 000 contains preliminary test data. Folders 011..014 contain data for testing the system.</p> <ul> <li>000 and 003 were shot with an handheld cellphone.</li> <li>001 and 002 were shot with 3 GOPRO Hero 3 cameras, fixed on the head with straps.</li> <li>004..014 were shot with 3 Bluefox cameras, fixed on a rigid helm (the same model and with the same lens as the camera mounted on the quadcopter).</li> </ul>
Fast Trajectory End-Point Prediction with Event Cameras for Reactive Robot Control
<p>If you use any of this data, please cite the following publication:</p> <p><span>@inproceedings{monforte2023fast,</span><br><span> title={Fast Trajectory End-Point Prediction with Event Cameras for Reactive Robot Control},</span><br><span> author={Monforte, Marco and Gava, Luna and Iacono, Massimiliano and Glover, Arren and Bartolozzi, Chiara},</span><br><span> booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},</span><br><span> pages={4035--4043},</span><br><span> year={2023}</span><br><span>}</span></p> <p>Event-based datasets of synthetic and real trajectories of a bouncing ball.</p> <p>The synthetic trajectories were obtained converting frames taken using Unreal Engine to events. The ground truth is provided along with objects and camera settings.</p> <p>The real trajectories wer dumped from a real event camera located in front of the robot workspace.</p> <p>To import .log files containing events, we suggest <a href="https://github.com/event-driven-robotics/bimvee">bimvee</a> Python library.</p> <p>Specifically use the functions to import .log files:</p> <p>data = importIitYarpBinaryDataLog(filePathOrName=input_path)<br> </p> <p> </p> <p> </p>
Supplementary Video for Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning
<p>This file contains video of the real world experiments presented in the paper "Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning". </p> <p>It also provides a high-level overview of the motivation and the theory developed in the paper.<br> </p>
SC3.2 Smart Robot teaser
<p>Thos video shows an overview of SC3.2 developments within AI4DI project.</p>
Passively Addressed Robotic Morphing Surface (PARMS) based on machine learning
<p>Reconfigurable morphing surfaces provide new opportunities for advanced human-machine interfaces and bio-inspired robotics. Morphing into arbitrary surfaces on demand requires a device with a sufficiently large number of actuators and an inverse control strategy that can calculate the actuator stimulation necessary to achieve a target surface. The programmability of a morphing surface can be improved by increasing the number of independent actuators, but this increases the complexity of the control system. Thus, developing compact and efficient control interfaces and control algorithms is a crucial knowledge gap for the adoption of morphing surfaces in broad applications. In this work, we describe a passively addressed robotic morphing surface (PARMS) composed of matrix-arranged ionic actuators. To reduce the complexity of the physical control interface, we introduce passive matrix addressing. Matrix addressing allows the control of N<sup>2</sup> independent actuators using only 2N control inputs, which is significantly lower than N<sup>2</sup> control inputs required for traditional direct addressing. Our control algorithm is based on machine learning using finite element simulations as the training data. This machine-learning approach allows both forward and inverse control with high precision in real time. Inverse control demonstrations show that the PARMS can dynamically morph into target surfaces on demand. These innovations in actuator matrix control may enable future implementation of PARMS in wearables, haptics, and augmented reality/virtual reality (AR/VR).</p>
Robotic extrahepatic Glissonean pedicle isolation focusing on Laennec's capsule for anatomic liver resection: short-term surgical outcomes
<p>We will submit an article for publication in the <em>Journal of Personalized Medicine, </em>titled <strong>“</strong><strong>Robotic extrahepatic Glissonean pedicle isolation focusing on Laennec's capsule for anatomic liver resection: short-term surgical outcomes</strong><strong>” </strong></p> <p>This article describes the utility of the Glissonean pedicle isolation as an Inflow control in anatomic liver resection. We examined Laennec's capsule surrounding the Glissonean pedicle. Furthermore, we found that the use of a recently developed surgical robotic system may reduce the difficulty and improve the safety of the procedure. These files are video clips of Glissonan pedicle isolation in laparoscopic and robotic surgery.</p> <p><strong>Supplementary file 1.</strong> Laparoscopic extrahepatic left Glissonean pedicle isolation in cadaveric models.</p> <p><strong>Supplementary file 2.</strong> Laparoscopic extrahepatic right anterior and posterior Glissonean pedicle isolation. </p> <p><strong>Supplementary file 3.</strong> Laparoscopic extrahepatic Glissonean pedicle 8 isolation.</p> <p><strong>Supplementary file 4.</strong> Robotic extrahepatic right posterior Glissonean pedicle isolation.</p> <p><strong>Supplementary file 5.</strong> Robotic extrahepatic Glissonean pedicle 4a, 4b, and 4c isolation.</p>
Data repository Childprogramming + Debugging + Robotics
<p>Este repositorio de datos alberga información sobre las investigaciones realizadas en el marco de dos investigaciones relacionadas y centradas en el fomento del pensamiento computacional en la educación primaria mediante la metodología Childprogramming. El repositorio sirve de eje central para almacenar y organizar datos valiosos relativos a la aplicación de conceptos de depuración y robótica educativa. Contiene información relativa a los proyectos realizados en este ámbito. Incluye los resultados de los casos de estudio aplicados.</p> <p> </p>
Dataset - On the performance of online adaptation of robots controlled by nanowire networks
<p>Dataset of the experiments considered in the article in the title</p>
ScienceDex guides
Understand access before you commit
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.