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5 CONCLUSIONS
To conclude, this paper presented multi-modal per-
son detection and tracking from a mobile robot based
on LRF and vision intended for a socially accept-
able navigation in crowded scenes during a person
following activity. Though a person following sce-
nario is considered, the framework is applicable for
any service robot activity in a crowded public envi-
ronment where perception of the whereabouts and dy-
namics of the persons around is required. It has been
clearly shown that the multi-modal approach outper-
forms its single sensor counterparts taking detection,
subsequent use, computation time, and precision all
into account. Results obtained from offline and online
robotic experiments have also been clearly reported
asserting this statement.
Currently, investigations are on the way to use
a LadyBug2 spherical camera to improve the detec-
tion and tracking further taking advantage of its wide
field of view. Preliminary investigations are also un-
derway with navigational schemes that consider the
spatio-temporal information provided by our multi-
target tracker.
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