TY - GEN
T1 - Long-term human affordance maps
AU - Limosani, R.
AU - Morales, L. Yoichi
AU - Even, J.
AU - Ferreri, F.
AU - Watanabe, A.
AU - Cavallo, F.
AU - Dario, P.
AU - Hagita, N.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/11
Y1 - 2015/12/11
N2 - This paper presents a work on mapping the use of space by humans in long periods of time. Daily geometric maps with the same coordinate frame were generated with SLAM, and in a similar manner, daily affordance density maps (places people use) were generated with the output of a human tracker running on the robot. The contribution of the paper is two-fold: an approach to detect geometric changes to cluster them in similar geometric configurations and the building of geometric and affordance composite maps on each cluster. This approach avoids the loss of long term retrieved information. Geometric similarity was computed using a normal distance approach on the maps. The analysis was performed on data collected by a mobile robot for a period of 4 months accumulating data equivalent to 70 days. Experimental results show that the system is capable of detecting geometric changes in the environment and clustering similar geometric configurations.
AB - This paper presents a work on mapping the use of space by humans in long periods of time. Daily geometric maps with the same coordinate frame were generated with SLAM, and in a similar manner, daily affordance density maps (places people use) were generated with the output of a human tracker running on the robot. The contribution of the paper is two-fold: an approach to detect geometric changes to cluster them in similar geometric configurations and the building of geometric and affordance composite maps on each cluster. This approach avoids the loss of long term retrieved information. Geometric similarity was computed using a normal distance approach on the maps. The analysis was performed on data collected by a mobile robot for a period of 4 months accumulating data equivalent to 70 days. Experimental results show that the system is capable of detecting geometric changes in the environment and clustering similar geometric configurations.
UR - http://www.scopus.com/inward/record.url?scp=84958162425&partnerID=8YFLogxK
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U2 - 10.1109/IROS.2015.7354193
DO - 10.1109/IROS.2015.7354193
M3 - Conference contribution
AN - SCOPUS:84958162425
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 5748
EP - 5754
BT - IROS Hamburg 2015 - Conference Digest
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015
Y2 - 28 September 2015 through 2 October 2015
ER -