Yuto Mori

Multi-cue 3D object recognition in knowledge-based vision-guided humanoid robot system

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.

Task guided attention control and visual verification in tea serving by the daily assistive humanoid HRP2JSK

This paper describes daily assistive task experiments that conducting on the HRP2JSK humanoid robot. We present overall action and recognition integrated system design to realize daily assistive behaviors autonomously and robustly, along with the demonstration that the HRP2JSK pours tea from a bottle to a cup and wash it after human drink it. To obtain autonomy and robustness, visual recognition and behavior control through perception information are important.

System integration of a daily assistive robot and its application to tidying and cleaning rooms

This paper describes a software system integration of daily assistive robots. Several tasks related to cleaning and tidying up rooms are focused on. Recognition and motion generation functions needed to perform daily assistance are developed, and these functions are used to design various behaviors involved in daily assistance. In our approach, the robot behaviours are divided into simple units which consist of 3 functions as check/plan/do, it provides us with high reusable and flexible development environment. Because sequential task execution can be achieved only after functions about failure detection and recovery, we also try to implement such functions in keeping with this approach. In addition to using simple behavior unit, multilayer error handling is effective. Experiments doing several daily tasks with handling daily tools showed the effectiveness of our system.

Task and vision based online manipulator trajectory generation for a humanoid robot

This paper presents a method to generate vision and task based robot manipulator trajectories. In the framework of the research on daily assistive robots the task formulated for this work consists in ranging boxes in a shelf or picking them up and placing them into a shopping cart. For object recovery SIFT keypoint tracking in combination with stereo vision is used. A collision free trajectory between two way points is generated based on a 3D-gridmap of the environment in front of the robot. A trajectory generation loop is implemented using resolved motion rate control and attractor coordinate frames that define the way points of the trajectory. The proposed method was tested on the humanoid robot HRP2-JSK.

Tidying and cleaning rooms using a daily assistive robot

This paper describes a system integration of daily assistive robots. Several tasks related to cleaning and tidying up rooms are focused on. Recognition and motion generation functions were integrated onto the robot, and these provided failure detection and in some cases, its recovery. Experiments of several daily tasks handling daily tools showed the effectiveness of our system.