Skip to Main Content
A vision based object recognition subsystem on knowledge-based humanoid robot system is presented. Humanoid robot system for real world service application must integrate an object recognition subsystem and a motion planning subsystem in both mobility and manipulation tasks. These requirements involve the vision system capable of self-localization for navigation tasks and object recognition for manipulation tasks, while communicating with the motion planning subsystem. In this paper, we describe a design and implementation of knowledge based visual 3D object recognition system with multi-cue integration using particle filter technique. The particle filter provides very robust object recognition performance and knowledge based approach enables robot to perform both object localization and self localization with movable/fixed information. Since this object recognition subsystem share knowledge with a motion planning subsystem, we are able to generate vision-guided humanoid behaviors without considering visual processing functions. Finally, in order to demonstrate the generality of the system, we demonstrated several vision-based humanoid behavior experiments in a daily life environment.