@InProceedings{kwak:humanoids:2009,
  author    = {Kwak, Nosan and Stasse, Olivier and Foissotte, Tor{\'e}a and Yokoi, Kazuhito},
  title     = {3D Grid and Particle based SLAM for a Humanoid Robot},
  booktitle = {IEEE-RAS International Conference on Humanoid Robots},
  year      = {2009},
  pages     = {62--67},
  address   = {Paris, France},
  month     = {December 7-December 10},
  keywords  = {Simultaneous localization and mapping, Humanoid robots, Stereo vision, Computational efficiency, Path planning, Service robots, Intelligent robots, Tree data structures, Processor scheduling, Navigation},
  doi       = {10.1109/ICHR.2009.5379602},
  abstract  = {Necessity to recognize the world like a home environment by a humanoid robot has recently been arisen for daily usages. As an observation sensor, stereo vision is the most common device for a humanoid robot to obtain the environmental data, but it is more erroneous than a laser sensor. To overcome the inaccuracy of stereo vision, we propose a particle-based SLAM technique so that the SLAM posterior is estimated by multiple hypotheses. The major difficulty of the particle-based SLAM with 3D grid maps is the high computational cost. To reduce the computational cost, we also propose a scheduling method for the time when to match and for particles that engage in the matching process. Through experiments with a humanoid robot, HRP-2, it is shown that the proposed approach can reduce the computational cost while preserving estimation accuracy.}
}