A. P. Pobil, Majd Kassawat, A. J. Duran, M. Arias, N. Nechyporenko, Arijit Mallick, E. Cervera, Dipendra Subedi, Ilia Vasilev, D. Cardin, Emanuele Sansebastiano, Ester Martínez-Martín, A. Morales, Gustavo A. Casañ, A. Arenal, B. Goriatcheff, C. Rubert, G. Recatalá
{"title":"UJI RobInLab参加2017年亚马逊机器人挑战赛的方法","authors":"A. P. Pobil, Majd Kassawat, A. J. Duran, M. Arias, N. Nechyporenko, Arijit Mallick, E. Cervera, Dipendra Subedi, Ilia Vasilev, D. Cardin, Emanuele Sansebastiano, Ester Martínez-Martín, A. Morales, Gustavo A. Casañ, A. Arenal, B. Goriatcheff, C. Rubert, G. Recatalá","doi":"10.1109/MFI.2017.8170448","DOIUrl":null,"url":null,"abstract":"This paper describes the approach taken by the team from the Robotic Intelligence Laboratory at Jaume I University to the Amazon Robotics Challenge 2017. The goal of the challenge is to automate pick and place operations in unstructured environments, specifically the shelves in an Amazon warehouse. RobInLab's approach is based on a Baxter Research robot and a customized storage system. The system's modular architecture, based on ROS, allows communication between two computers, two Arduinos and the Baxter. It integrates 9 hardware components along with 10 different algorithms to accomplish the pick and stow tasks. We describe the main components and pipelines of the system, along with some experimental results.","PeriodicalId":402371,"journal":{"name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","volume":"329 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"UJI RobInLab's approach to the Amazon Robotics Challenge 2017\",\"authors\":\"A. P. Pobil, Majd Kassawat, A. J. Duran, M. Arias, N. Nechyporenko, Arijit Mallick, E. Cervera, Dipendra Subedi, Ilia Vasilev, D. Cardin, Emanuele Sansebastiano, Ester Martínez-Martín, A. Morales, Gustavo A. Casañ, A. Arenal, B. Goriatcheff, C. Rubert, G. Recatalá\",\"doi\":\"10.1109/MFI.2017.8170448\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the approach taken by the team from the Robotic Intelligence Laboratory at Jaume I University to the Amazon Robotics Challenge 2017. The goal of the challenge is to automate pick and place operations in unstructured environments, specifically the shelves in an Amazon warehouse. RobInLab's approach is based on a Baxter Research robot and a customized storage system. The system's modular architecture, based on ROS, allows communication between two computers, two Arduinos and the Baxter. It integrates 9 hardware components along with 10 different algorithms to accomplish the pick and stow tasks. We describe the main components and pipelines of the system, along with some experimental results.\",\"PeriodicalId\":402371,\"journal\":{\"name\":\"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)\",\"volume\":\"329 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MFI.2017.8170448\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MFI.2017.8170448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
UJI RobInLab's approach to the Amazon Robotics Challenge 2017
This paper describes the approach taken by the team from the Robotic Intelligence Laboratory at Jaume I University to the Amazon Robotics Challenge 2017. The goal of the challenge is to automate pick and place operations in unstructured environments, specifically the shelves in an Amazon warehouse. RobInLab's approach is based on a Baxter Research robot and a customized storage system. The system's modular architecture, based on ROS, allows communication between two computers, two Arduinos and the Baxter. It integrates 9 hardware components along with 10 different algorithms to accomplish the pick and stow tasks. We describe the main components and pipelines of the system, along with some experimental results.
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