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
复制标题
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:
影响因子:
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通讯作者:
F. Kanehiro
中科院分区:
文献类型:
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作者:
Iori Kumagai;Fumihito Sugai;Shunichi Nozawa;Youhei Kakiuchi;K. Okada;M. Inaba;F. Kanehiro
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.
影响因子:
3.5
作者:
Hornung, Armin;Wurm, Kai M.;Burgard, Wolfram
通讯作者:
Burgard, Wolfram