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[2I6-OS-4a-03] Automation and Execution of Fetch-and-Carry Tasks Based on Multi-Modal Language Processing
Keywords:Fetch-and-carry Task, Object Grounding, Multimodal Language Processing, Vision & Language, Domestic Service Robots
The practical use of domestic support robots that can naturally communicate with users to assist with daily tasks is one promising solution for support recipients. However, the ability of domestic support robots to understand natural language instructions and properly perform daily tasks is currently insufficient. In this paper, we aim to construct methods for robots to execute instructions given in natural language for fetch-and-carry tasks. Therefore, we propose a method that can be applied to tasks where multiple target objects and target areas are input and the best candidate is predicted by expanding existing methods. Additionally, by incorporating an instruction generation model, we make it possible to conduct simulations on-the-fly. In experiments, we achieved performance that exceeded existing methods in understanding instructions and confirmed that the task was executed properly.
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