Case-based reasoning emulation of persons for wheelchair navigation

Peula, J.M.; García, Cristina; Herrero, Ignacio; Fernández-Carmona, Manuel; Hernández, Francisco

doi:10.1016/j.artmed.2012.08.007

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…As commented by different authors [6]- [8] a complex behavior can be modeled via the combination of simple ones. The main advantage of the use of basic behaviors is that they are less sensitive to sensor errors, more generic, easier to develop and test and adapt better to most situations and environments [15].…”

Section: Coordination By Learningmentioning

confidence: 98%

“…On the other hand, in implicit coordination each robot acts on its own taking into account the existence of the others and even sharing information between themwhere they are or what they see-, but without explicitly making decisions together. In this case, coordination is normally achieved in the form of an emergent behavior, arisen from the combination of simpler ones [6]- [8]. This kind of coordination is easier to achieve through training, as it only requires to train a robot simultaneously, while the others act on their own.…”

Section: Introductionmentioning

confidence: 98%

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Implicit robot coordination using Case-Based Reasoning behaviors

Peula

García

Herrero

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Multi-robot systems (MRS) are a very active and important research topic nowadays. One of the main problems of these systems is the large number of variables to take into account. Due to this, robot behaviors are sometimes learnt instead of calculated via analytical expressions. A typical learning mechanism, specially for biomimetic robots, is Learning from demonstration (LfD). This paper proposes a LfD approach for implicit coordinated navigation using combination of CaseBased Reasoning (CBR) behaviors. During a training stage, CBR is used to learn simple behaviors that associate positions of other robots and/or objects to motion commands for each robot. Thus, human operators only need to concentrate on achieving their robot's goal as efficiently as possible in the operating conditions. Then, in running stage, each robot will achieve a different coordinate navigation strategy depending on the triggered behaviors. This system has been successfully tested with three Aibo-ERS7 robots in a RobCup-like environment.

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Section: Coordination By Learningmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%