From place detection to long-term place memory

Abstract

This thesis is concerned with automated place detection and its coupling with long-term place memory. Long-term place memory is critical if a robot is to be placeaware as it stores the relevant knowledge for future referral. Place detection is closely coupled to place memory as it determines the appearances belonging to each place and thus plays a key role in regards to which knowledge gets retained in the long-term place memory. In this perspective, the contributions of the thesis are as follows: First, it introduces a novel approach to place detection based on coherent visual segments. Second, a new approach to place representation referred to as `segments summary graph' is presented. Finally, it is shown that this representation can be utilized for improving the reliability of memory association.