Spatio-Temporal Case-Based Reasoning for Behavioral Selection
Abstract
This paper presents the application of a Case-Based Reasoning
approach to the selection and modification of behavioral
assemblage parameters. The goal of this research is to achieve an
optimal parameterization of robotic behaviors in run-time. This
increases robot performance and makes a manual configuration
of parameters unnecessary. The case-based reasoning module
selects a set of parameters for an active behavioral assemblage in
real-time. This set of parameters fits the environment better than
hand-coded ones, and its performance is monitored providing
feedback for a possible reselection of the parameters. This paper
places a significant emphasis on the technical details of the case-based
reasoning module and how it is integrated within a schema-based
reactive navigation system. The paper also presents the
results and evaluation of the system in both in simulation and real
world robotic experiments.