Spatio-Temporal Case-Based Reasoning for Behavioral Selection
Maxim Likhachev and Ronald C. Arkin
Mobile Robot Laboratory
College of Computing, Georgia Institute of Technology
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 reduce the process of defining a large set of robotic behaviors to defining only a small set of orthogonal behaviors. 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.
Index terms: Case-Based Reasoning, Behavior-Based Robotics, Reactive Robotics.