MQA: Answering the Question via Robotic Manipulation
Abstract
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.