Path Planning with Obstacle Avoidance Based on Normalized R-Functions
Joint Authors
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Existing methods for path planning with obstacle avoidance need to check having the interference between a moving part and an obstacle at iteration and even to calculate their shortest distance in the case of given motion parameters.
Besides, the tasks like collision-checking and minimum-distance calculating themselves are complicated and time-consuming.
Rigorous mathematical analysis might be a practical way for dealing with the above-mentioned problems.
An R-function is a real-valued function whose properties are fully determined by corresponding attributes of their parameters, which is usually applied to express a geometrical object.
Thus, a signed distance function based on R-functions is created to represent whether two objects intervene and their level of intervention or separation.
As the signed function is continuous and differentiable, the gradient information of the objective function guides a moving part to avoid its obstacles and to approach its target position rapidly.
Therefore, a path planning approach with obstacle avoidance based on normalized R-functions is proposed in this paper.
A discrete convex hull approach is adopted to solve the problem that R-function is inappropriate to represent a geometric object with some curves or surfaces, and pendent points and edges are generated in Boolean operations.
Besides, a normalized approach ensures accuracy calculation of signed distance function.
Experimental results have shown that the presented approach is a feasible way for path planning with obstacle avoidance.
American Psychological Association (APA)
Tao, Songqiao& Tan, Juan. 2018. Path Planning with Obstacle Avoidance Based on Normalized R-Functions. Journal of Robotics،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1197836
Modern Language Association (MLA)
Tao, Songqiao& Tan, Juan. Path Planning with Obstacle Avoidance Based on Normalized R-Functions. Journal of Robotics No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1197836
American Medical Association (AMA)
Tao, Songqiao& Tan, Juan. Path Planning with Obstacle Avoidance Based on Normalized R-Functions. Journal of Robotics. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1197836
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197836