Satoru Tokutsu

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.

Environment situation reasoning integrating human recognition and life sound recognition using DBN

Humanoid robots for home daily assistance need to have an autonomous behavior selection system. To realize this, situation recognition capability is important. In this paper, we propose a situation recognition system where the use of daily life sounds enables to recognize situations difficult to understand using only visual sensor data and where the use of time series of information enables robust situation recognition. We apply cepstrum feature for recognition of daily life sounds and Dynamic Bayesian Networks(DBN) for robust situation recognition. As an example of situation recognition, we show some experiments and results targeting some situations that a human is in a kitchen.

Enhanced Mother Environment with Humanoid Specialization in IRT Robot Systems

In the research to realize high standard task-oriented assistant robots, a general and strategic way of development is essential. Otherwise high functionality and potential for evolution of those robots cannot be achieved. Robotic systems are socially expected to assist our daily life in many situations. As a result, projects related to those robots are becoming large, involving many researchers and engineers of universities and companies. This motivated us a new strategy to construct robotic systems based on mother environment and humanoid specialization to keep developing and refining functional elements of robots in an evolutionary way. The mother environment is an entity that creates brains of humanoid robots, where various robotics function elements, libraries, middle-wares and other research tools are integrated. Then the brain of each robot is developed utilizing the functional elements in the mother. We call this process specialization of a humanoid. To enhance this specialization process, we introduce a generator, which realizes conversion of functions in the mother environment for the real-time layer. After the research of these specific robots, enhanced robotics functions are incorporated into the mother again. We call this process feedback. In this chapter, we present these ideas using concrete implementation examples in IRT projects[1], where several robots to assist our daily life are developed.