TY - GEN
T1 - A perceptual memory system for grounding semantic representations in intelligent service robots
AU - Oliveira, Miguel
AU - Lim, Gi Hyun
AU - Lopes, Luis Seabra
AU - Kasaei, S.H.
AU - Tome, Ana Maria
AU - Chauhan, Aneesh
PY - 2014/10/31
Y1 - 2014/10/31
N2 - This paper addresses the problem of grounding semantic representations in intelligent service robots. In particular, this work contributes to addressing two important aspects, namely the anchoring of object symbols into the perception of the objects and the grounding of object category symbols into the perception of known instances of the categories. The paper discusses memory requirements for storing both semantic and perceptual data and, based on the analysis of these requirements, proposes an approach based on two memory components, namely a semantic memory and a perceptual memory. The perception, memory, learning and interaction capabilities, and the perceptual memory, are the main focus of the paper. Three main design options address the key computational issues involved in processing and storing perception data: a lightweight, NoSQL database, is used to implement the perceptual memory; a thread-based approach with zero copy transport of messages is used in implementing the modules; and a multiplexing scheme, for the processing of the different objects in the scene, enables parallelization. The system is designed to acquire new object categories in an incremental and open-ended way based on user-mediated experiences. The system is fully integrated in a broader robot system comprising low-level control and reactivity to high-level reasoning and learning.
AB - This paper addresses the problem of grounding semantic representations in intelligent service robots. In particular, this work contributes to addressing two important aspects, namely the anchoring of object symbols into the perception of the objects and the grounding of object category symbols into the perception of known instances of the categories. The paper discusses memory requirements for storing both semantic and perceptual data and, based on the analysis of these requirements, proposes an approach based on two memory components, namely a semantic memory and a perceptual memory. The perception, memory, learning and interaction capabilities, and the perceptual memory, are the main focus of the paper. Three main design options address the key computational issues involved in processing and storing perception data: a lightweight, NoSQL database, is used to implement the perceptual memory; a thread-based approach with zero copy transport of messages is used in implementing the modules; and a multiplexing scheme, for the processing of the different objects in the scene, enables parallelization. The system is designed to acquire new object categories in an incremental and open-ended way based on user-mediated experiences. The system is fully integrated in a broader robot system comprising low-level control and reactivity to high-level reasoning and learning.
U2 - 10.1109/IROS.2014.6942861
DO - 10.1109/IROS.2014.6942861
M3 - Conference paper
AN - SCOPUS:84911489131
SN - 9781479969340
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2216
EP - 2223
BT - IROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
Y2 - 14 September 2014 through 18 September 2014
ER -