Achieving intelligence in mobility : Incorporating warning capabilities in real-world mobile robots
This paper presents an integrated approach to the application of machine learning techniques for the enhancement of mobile robots' skills. It identifies the learning tasks that can be observed throughout a number of typical applications of mobile robots and puts those tasks into perspective with respect to both existing and newly developed learning techniques. The actual realisation of the approach has been carried out on the two mobile robots PRIAMOS and TESEO, which are both operating in a real office environment. In this context, several experimental results are presented.
Bibliographic Reference: Article: IEEE Expert : Intelligent Robotic Systems (1995)
Record Number: 199511170 / Last updated on: 1995-08-23
Original language: en
Available languages: en