MQA: Answering the Question via Robotic Manipulation
In: Robotics: Science and Systems; (2020-03-10)
Online
unknown
Zugriff:
In this paper, we propose a novel task, Manipulation Question Answering (MQA), where the robot performs manipulation actions to change the environment in order to answer a given question. To solve this problem, a framework consisting of a QA module and a manipulation module is proposed. For the QA module, we adopt the method for the Visual Question Answering (VQA) task. For the manipulation module, a Deep Q Network (DQN) model is designed to generate manipulation actions for the robot to interact with the environment. We consider the situation where the robot continuously manipulating objects inside a bin until the answer to the question is found. Besides, a novel dataset that contains a variety of object models, scenarios and corresponding question-answer pairs is established in a simulation environment. Extensive experiments have been conducted to validate the effectiveness of the proposed framework.
has been accepted by Robotics: Science and Systems 2021
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MQA: Answering the Question via Robotic Manipulation
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Autor/in / Beteiligte Person: | Guo, Di ; Liu, Huaping ; Deng, Yuhong ; Sun, Fuchun ; Zhang, Naifu ; Guo, Xiaofeng |
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Quelle: | Robotics: Science and Systems; (2020-03-10) |
Veröffentlichung: | 2020 |
Medientyp: | unknown |
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