Name
Abstract | ||
|---|---|---|
This paper presents an approach to imitation learning in robotics focusing on low level behaviours, so that they do not need to be encoded into sets and rules, but learnt in an intuitive way. Its main novelty is that, rather than trying to analyse natural human actions and adapting them to robot kinematics, humans adapt themselves to the robot via a proper interface to make it perform the desired action. As an example, we present a successful experiment to learn a purely reactive navigation behaviour using robotic platforms. Using Case Based Reasoning, the platform learns from a human driver how to behave in the presence of obstacles, so that no kinematics studies or explicit rules are required. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/s10339-005-0004-z | Cognitive processing |
Keywords | Field | DocType |
supervised learning æ adaptation æ case based reasoning æ reactive navigation æ teaching,use case,supervised learning,case base reasoning | Robot learning,Computer science,Robot kinematics,Cognitive imitation,Situated robotics,Imitation,Artificial intelligence,Case-based reasoning,Robot,Robotics | Journal |
Volume | Issue | ISSN |
6 | 3 | 1612-4782 |
Citations | PageRank | References |
1 | 0.37 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| C. Urdiales | 1 | 251 | 33.14 |
| Ulises Cortés | 2 | 619 | 98.84 |