{"data":{"id":"10.6084/m9.figshare.8953124","type":"dois","attributes":{"doi":"10.6084/m9.figshare.8953124","prefix":"10.6084","suffix":"m9.figshare.8953124","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Aran Sena","affiliation":[],"nameIdentifiers":[]},{"name":"Howard, Matthew","nameType":"Personal","givenName":"Matthew","familyName":"Howard","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Demonstration Tray Data"}],"publisher":"figshare","container":{},"publicationYear":2019,"subjects":[{"subject":"90602 Control Systems, Robotics and Automation","subjectScheme":"FOR"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"170203 Knowledge Representation and Machine Learning","subjectScheme":"FOR"},{"subject":"FOS: Psychology","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Psychology","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"109999 Technology not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Other engineering and technologies","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Other engineering and technologies","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Artificial Intelligence and Image Processing"},{"subject":"FOS: Computer and information sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"80602 Computer-Human Interaction","subjectScheme":"FOR"},{"subject":"Applied Computer Science"},{"subject":"70699 Horticultural Production not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Agriculture, forestry and fisheries","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Agriculture, forestry and fisheries","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2019-07-18","dateType":"Created"},{"date":"2019-07-18","dateType":"Updated"},{"date":"2019","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["1460797103 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Data stored in a zipped ~1.5Gb MATLAB .mat file.\u003cbr\u003e---\u003cbr\u003eSee [Sena, Howard 2019] for full details on data collection, summary below (link 1 in references).\u003cbr\u003e---\u003cbr\u003eData formatted to follow similar internal 's' structure as [Calinon 2015] (link 2 in references).\u003cbr\u003e\u003cbr\u003e----\u003cbr\u003eLoads a struct 'groups'. Contains data from a 4 x 3 mixed ANOVA style study.\u003cbr\u003eCondition 1: No FeedbackCondition 2: Replay FeedbackCondition 3: Batch FeedbackCondition 4: Selected Feedback\u003cbr\u003eSee [Sena, Howard 2019] for full details on test conditions (link 1 in references).\u003cbr\u003e\u003cbr\u003e----\u003cbr\u003eData collected from novice participants using a Rethink Robotics Sawyer collaborative robot to perform a horticultural tray sorting manipulation task. \u003cbr\u003e---\u003cbr\u003e4 groups, one for each condition.Each group contains:- demos : Set of data collected from users-- Each row in demos represents a participant.-- Each column represents an attempt at the assigned condition.-- Contains sub structs containing the experiment data for each attempt (demonstration data trajectories, etc.)- repos : Set of data generated with TP-GMR model, as described in [Sena, Howard 2019]-- Rows and columns same as demos, but all data is generated from the model.-- Same sub structs as demos, except there will be 100 trajectories (one for each target plant in the experiment tray).\u003cbr\u003e---\u003cbr\u003eThis experiment was conducted with ethical approval granted by King's College London Research Ethics Committee under LRS-17/18-5549.\u003cbr\u003e","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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