NDLI: Robot path planning with distance-safety criterion

Content Provider	IEEE Xplore Digital Library
Author	Suk-Hwan Suh Shin, K.G.
Copyright Year	1987
Description	Author affiliation: University of Michigan, Ann Arbor, MI (Suk-Hwan Suh; Shin, K.G.)
Abstract	Euclidean distance is the most popular criterion for robot path planning. However, the shortest path (SP) is dangerous in some cases because such a path drives the robot too close to obstacles. When safety is the main concern, a center-line path (CLP) providing the maximum clearance from obstacles would be preferable over the SP, although the length of a CLP could be considerably longer than that of a SP. Since the SP and CLP are two extremes with respect to the distance and safety criteria, respectively, it would be useful in practice to strike a compromise between the two criteria. The purpose of this paper is to develop a method for determining an optimal path with a weighted distance-safety criterion. The method is composed of three parts: (i) construction of a region map by dividing the workspace, (ii) inter-region optimization to determine the entry and departure points of the path in each region, and (iii) intra-region optimization for determining the (optimal) path segment within each region. The region map is generated by using an approximate Voronoi diagram, and the inter- (intra-) region optimization is achieved by using the variational dynamic programming. Although it is developed for 2D problems, our method can be easily extended to a class of 3D problems. Numerical examples are also presented to demonstrate the method.
Starting Page	634
Ending Page	641
File Size	693658
Page Count	8
File Format	PDF
DOI	10.1109/CDC.1987.272915
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1987-12-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robots Path planning Safety Optimization methods Dynamic programming Euclidean distance Uncertainty Manufacturing Drives Joining processes
Content Type	Text
Resource Type	Article

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