Contextual task-aware shared autonomy for assistive mobile robot teleoperation
Contextual task-aware shared autonomy for assistive mobile robot teleoperation
复制标题
辅助移动机器人远程操作的上下文任务感知共享自主权
DOI：
10.1109/iros.2014.6943023
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Johann Marius Zöllner
中科院分区：
文献类型：
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作者：
Ming Gao;Jan Oberländer;T. Schamm;Johann Marius Zöllner
对于机器人在未知甚至危险环境中的应用，例如搜索和救援，对于人类来说，仅仅简单地遥控移动的机器人而没有其帮助是困难和有压力的。因此，促进人类和机器人之间有效共享自主权的方法是机器人领域中许多研究工作的主题。本文提出了一种新的共享自治系统，该系统通过估计用户正在执行的任务的上下文信息的基础上，识别用户的意图，并根据推理提供运动辅助。为了考虑上下文任务识别的不确定性，采用高斯混合回归模型结合递归贝叶斯滤波器，自适应于操作过程中任务执行的隐式用户模型。所提出的方法适用于控制飞行机器人的两种任务类型的背景下：门口交叉和对象检查的问题。仿真结果证明了该方法的有效性。
For robot applications in unknown or even hazardous environments, such as search and rescue, it is difficult and stressful for human beings to merely simply teleoperate a mobile robot without its assistance. Consequently, means to facilitate an efficient shared autonomy between human and robot are the subject of much research work in the field of robotics. This paper proposes a novel shared autonomy system, which recognizes the user intention by estimating the task the user is executing based on the context information, and provides motion assistance according to the inferences. To incorporate the uncertainty of contextual task recognition, a Gaussian Mixture Regression model combined with a recursive Bayesian filter is adopted, which is adaptive to the implicit user model for task execution during operation. The proposed method is applied to the problem of controlling a flying robot in the context of two task types: doorway crossing and object inspection. Its benefits are demonstrated by the simulation results.