Complementary integration framework for localization and recognition of a humanoid robot based on task-oriented frequency and accuracy requirements

Complementary integration framework for localization and recognition of a humanoid robot based on task-oriented frequency and accuracy requirements
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基于任务导向的频率和精度要求的人形机器人定位和识别的补充集成框架

DOI:
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发表时间:
2017
期刊:
IEEE-RAS International Conference on Humanoid Robots
影响因子:
--
通讯作者:
F. Kanehiro
F. Kanehiro
中科院分区:
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文献类型:
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作者:
Iori Kumagai;Fumihito Sugai;Shunichi Nozawa;Youhei Kakiuchi;K. Okada;M. Inaba;F. Kanehiro

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一个能够在移动过程中进行环境测量和运动规划的机器人系统是连续执行各种任务所必需的。为了实现这样一个系统,我们称之为遍历中感知模型,必须提高环境识别的准确性,必须降低计算成本;这些都是权衡关系。在本文中,我们提出了一个类人机器人的构建框架,以解决权衡问题,并实现了在遍历中感知模型系统。该框架的核心思想是基于面向任务的频率和精度要求,以互补的方式细分和重新整合定位和识别过程。此外,我们将我们的框架应用于仿人机器人Jaxon,并证明了它可以通过遍历中感知模型连续执行各种任务。我们的框架最重要的贡献是使类人机器人能够准确地定位自己,并足够密集地测量环境,以便使用其车载计算机执行任务;这为识别质量和计算成本之间的权衡提供了一种实用的解决方案。
A robot system that can process environmental measurements and motion planning during locomotion is necessary to continuously perform various tasks. To achieve such a system, which we call the Perception-during-Traversing Model, the accuracy of environmental recognition must be improved and computational costs must be reduced; these are tradeoff relationships. In this paper, we propose a construction framework for a humanoid robot to solve the trade-off problems and achieve the Perception-during-Traversing Model system. The key idea of the proposed framework is subdividing and re-integrating the localization and recognition processes in a complementary manner based on task-oriented frequency and accuracy requirements. Moreover, we apply our framework to the humanoid robot JAXON, and demonstrate that it can execute various tasks continuously by the Perception-during-Traversing Model. The most important contribution of our framework is enabling the humanoid robot to localize itself accurately and measure the environment densely enough to execute tasks using its on-board computers; this provides a practical solution to the trade-off between recognition quality and computational costs.
DOI: 10.1007/s10514-012-9321-0
发表时间: 2013-04-01
期刊: AUTONOMOUS ROBOTS
影响因子: 3.5
作者:
Hornung, Armin;Wurm, Kai M.;Burgard, Wolfram
通讯作者: Burgard, Wolfram