@InProceedings{kumagai:humanoids:2017,
  author    = {Kumagai, Iori and Sugai, Fumihito and Nozawa, Shunnichi and Kakiuchi, Yohei and Okada, Kei and Inaba, Masayuki and Kanehiro, Fumio},
  title     = {Complementary Integration Framework of Localization and Recognition for a Humanoid Robot Based on Task-Oriented Frequency and Accuracy Requirement},
  booktitle = {IEEE-RAS International Conference on Humanoid Robots},
  year      = {2017},
  pages     = {683--688},
  address   = {Birmingham, England},
  month     = {November 15-November 17},
  keywords  = {Humanoid robots, Three-dimensional displays, Computational efficiency, Computational modeling, Planning},
  doi       = {10.1109/HUMANOIDS.2017.8246946},
  abstract  = {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.}
}