Teaching Humanoid Robots to Assist Humans for Collaborative Tasks
Teaching Humanoid Robots to Assist Humans for Collaborative Tasks
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DOI：
10.1109/smartcomp58114.2023.00083
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
J. Rodano;Omar Obidat;Jesse Parron;Rui Li;Michelle Zhu;Weitian Wang
中科院分区：
文献类型：
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作者：
J. Rodano;Omar Obidat;Jesse Parron;Rui Li;Michelle Zhu;Weitian Wang
随着技术的进步，社会已经见证并参与了能够行走，说话和识别语音的机器人的创造。为了促进人类和类人机器人之间的交流和协作，我们开发了一个教-学框架，人类教类人机器人完成物体识别和操作任务。机器人基于迁移学习方法向人类伙伴学习，并可以帮助人类使用他们学到的知识。实验结果和评估表明，在智能服务环境中的人机合作伙伴关系的成功和效率的方法。最后对今后的研究工作进行了展望。
As technology has advanced, society has witnessed and participated in the creation of robots that can walk, talk, and recognize speech. To facilitate communication and collaboration between humans and humanoid robots, we develop a teaching-learning framework for human beings to teach humanoid robots to complete object identification and operation tasks. The robots learn from their human partners based on the transfer learning approach and can assist humans using their learned knowledge. Experimental results and evaluations suggest the success and efficiency of the developed approach in smart service contexts for human-robot partnerships. The future work of this study is also discussed.