DocumentCode :
2939918
Title :
Autonomous robotic exploration using occupancy grid maps and graph SLAM based on Shannon and Rényi Entropy
Author :
Carrillo, Henry ; Dames, Philip ; Kumar, Vijay ; Castellanos, Jose A.
Author_Institution :
Depto. de Ing. Electron., Pontificia Univ. Javeriana, Bogota, Colombia
fYear :
2015
fDate :
26-30 May 2015
Firstpage :
487
Lastpage :
494
Abstract :
In this paper we examine the problem of autonomously exploring and mapping an environment using a mobile robot. The robot uses a graph-based SLAM system to perform mapping and represents the map as an occupancy grid. In this setting, the robot must trade-off between exploring new area to complete the task and exploiting the existing information to maintain good localization. Selecting actions that decrease the map uncertainty while not significantly increasing the robot´s localization uncertainty is challenging. We present a novel information-theoretic utility function that uses both Shannon´s and Rényi´s definitions of entropy to jointly consider the uncertainty of the robot and the map. This allows us to fuse both uncertainties without the use of manual tuning. We present simulations and experiments comparing the proposed utility function to state-of-the-art utility functions, which only use Shannon´s entropy. We show that by using the proposed utility function, the robot and map uncertainties are smaller than using other existing methods.
Keywords :
SLAM (robots); graph theory; mobile robots; Rényi entropy; Rényi´s definitions; Shannon definition; Shannon entropy; autonomous robotic exploration; graph based SLAM system; manual tuning; map uncertainty; mobile robot; occupancy grid maps; robot localization uncertainty; utility function; Covariance matrices; Entropy; Measurement uncertainty; Simultaneous localization and mapping; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2015 IEEE International Conference on
Conference_Location :
Seattle, WA
Type :
conf
DOI :
10.1109/ICRA.2015.7139224
Filename :
7139224
Link To Document :
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