Name
Abstract | ||
|---|---|---|
In this paper, we propose a framework towards the integration of information sensors based on the idea that the stimulus perceived through different sensors are spatial-time correlated for a short time period. Applications in robotics need to be able to process information from multiple sensors, for instance, in the case of a visible talking person. How can we relate those kind of information in a simple way, without making use of high level representation? This is the question that we want to address. A new framework based on correlation measure at low level data information is proposed. This ion: level correlation measure can be used as integration data engine to support high level task description. In this paper a coherent approach from sensor lever to task level for developing a robot which can handle a large number of sensors and actuators is developed. An example how this approach can be used for a visual-sound integration task is also presented. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/IROS.2000.895224 | 2000 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2000), VOLS 1-3, PROCEEDINGS |
Keywords | Field | DocType |
spatial-time information, correlation measure, sensor integration, humanoid robot, learning | Computer vision,Motion control,Image sensor,Computer science,Sensor fusion,Artificial intelligence,Sensory system,Robot,Robotics,Humanoid robot,Actuator | Conference |
Citations | PageRank | References |
2 | 0.55 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iris Fermin | 1 | 45 | 8.00 |
| Hiroshi G. Okuno | 2 | 2092 | 233.19 |
| Hiroshi Ishiguro | 3 | 2 | 0.55 |
| Hiroaki Kitano | 4 | 3515 | 539.37 |