From place detection to long-term place memory

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 place-aware 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.