Name
Abstract | ||
|---|---|---|
In order to have a robotic system able to effectively learn by imitation, and not merely reproduce the movements of a human teacher, the system should have the capabilities of deeply understanding the perceived actions to be imitated. This paper deals with the development of a cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. The purpose of the following discussion is to show how the same conceptual representation can be used both in a bottom-up approach, in order to learn sequences of actions by imitation learning paradigm, and in a top-down approach, in order to anchor the symbolical representations to the perceptual activities of the robotic system. The proposed architecture has been tested on the robotic system composed of a PUMA 200 industrial manipulator and an anthropomorphic robotic hand. The system demonstrated the ability to learn and imitate a set of movement primitives acquired through the vision system for simple manipulative purposes. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11558590_50 | AI*IA |
Keywords | Field | DocType |
symbolical representation,cognitive architecture,anthropomorphic robotic hand,rich conceptual representation,top-down approach,robotic system,vision system,conceptual representation,conceptual space,bottom-up approach,proposed architecture,bottom up,top down | Architecture,Machine vision,Computer science,Cognitive imitation,Human–computer interaction,Artificial intelligence,Imitation,Cognitive architecture,Perception,Cognitive development,Robotics,Distributed computing | Conference |
Volume | ISSN | ISBN |
3673 | 0302-9743 | 3-540-29041-9 |
Citations | PageRank | References |
4 | 0.43 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Chella | 1 | 374 | 65.74 |
| Haris Dindo | 2 | 125 | 17.49 |
| Ignazio Infantino | 3 | 151 | 32.13 |