NDLI: Efficient Exploration Algorithms for Rough Terrain Modeling Using Triangular Mesh Maps

Content Provider	IEEE Xplore Digital Library
Author	Lifang Liu Crowe, T.G. Bakambu, J.N.
Copyright Year	2008
Description	Author affiliation: Agric. & Bioresource Eng., Univ. of Saskatchewan, Saskatoon, SK (Lifang Liu; Crowe, T.G.) \|\| MacDonald, Dettwiler & Assoc. Ltd., Brampton, ON (Bakambu, J.N.)
Abstract	The objective of this paper is to exploit the potential of considering the information gain in greedy mapping strategies based on a triangular mesh map for automatic modeling of a large rough outdoor environment. An energy cost function is used to represent the travel cost and two methods to estimate possible new terrain in one spot using a 3D image sensor are described. For the first method, assuming a partly known environment, the information gain is estimated by applying the ray tracing algorithm to the known part of the environment. For the second method, the new information gain is calculated using polygon clipping in an unknown environment. Simulation results in a typical rough agricultural field showed that the exploration strategy, which was incorporated with energy consumption and the information gain estimation with a ray tracing algorithm using a coarse map, had an advantage over other polices in terms of energy consumption and the path length.
Starting Page	1206
Ending Page	1211
File Size	4375220
Page Count	6
File Format	PDF
ISBN	9781424416752
DOI	10.1109/RAMECH.2008.4681352
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot sensing systems Energy consumption Cost function Image sensors Ray tracing Extraterrestrial measurements Agricultural engineering Power engineering and energy Terrain mapping Path planning energy cost coverage path planning rough environment exploration Dijkstra shortest path
Content Type	Text
Resource Type	Article

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