{"title":"When Robots Meet Artificial Intelligence: Let’s Do Better to Gain People’s Trust [From the Editor’s Desk]","authors":"Yi Guo","doi":"10.1109/mra.2024.3428148","DOIUrl":null,"url":null,"abstract":"In a closed-door discussion that I attended recently, the award committee was debating whether to award the best student paper to a reinforcement learning-based robotics work with simulations using open datasets, or a robotics work using more traditional model-based methods with real robot experiments. Much more deliberation took place to reach the decision, and I’m not going to reveal which paper won the award, although, I must say both papers deserve recognition for being finalists in the competition. As a researcher who studied both classic dynamic model-based methods and machine learning-based methods to control robots, I have no bias toward either one, and I think the best solution for complex robotics problems may lie in better integrating of the two methods.","PeriodicalId":55019,"journal":{"name":"IEEE Robotics & Automation Magazine","volume":"52 1","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Robotics & Automation Magazine","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/mra.2024.3428148","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In a closed-door discussion that I attended recently, the award committee was debating whether to award the best student paper to a reinforcement learning-based robotics work with simulations using open datasets, or a robotics work using more traditional model-based methods with real robot experiments. Much more deliberation took place to reach the decision, and I’m not going to reveal which paper won the award, although, I must say both papers deserve recognition for being finalists in the competition. As a researcher who studied both classic dynamic model-based methods and machine learning-based methods to control robots, I have no bias toward either one, and I think the best solution for complex robotics problems may lie in better integrating of the two methods.
期刊介绍:
IEEE Robotics & Automation Magazine is a unique technology publication which is peer-reviewed, readable and substantive. The Magazine is a forum for articles which fall between the academic and theoretical orientation of scholarly journals and vendor sponsored trade publications. IEEE Transactions on Robotics and IEEE Transactions on Automation Science and Engineering publish advances in theory and experiment that underpin the science of robotics and automation. The Magazine complements these publications and seeks to present new scientific results to the practicing engineer through a focus on working systems and emphasizing creative solutions to real-world problems and highlighting implementation details. The Magazine publishes regular technical articles that undergo a peer review process overseen by the Magazine''s associate editors; special issues on important and emerging topics in which all articles are fully reviewed but managed by guest editors; tutorial articles written by leading experts in their field; and regular columns on topics including education, industry news, IEEE RAS news, technical and regional activity and a calendar of events.