A generalized real-time obstacle avoidance method without the cspace calculation

Yong-Ji Wang, Matthew Cartmell, Qui-Ming Tao, Han Liu

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

An important concept proposed in the early stage of robot path planning field is the shrinking of a robot to a point and meanwhile the expanding of obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision-free path for a point robot among the Cspace obstacles. However, the research experiences have shown that the Cspace transformation is very hard when the following situations occur: 1) both the robot and obstacles are not polygons, and 2) the robot is allowed to rotate. This situation gets even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. For this reason, direct path planning approaches without the Cspace transformation is quite useful and expected. Motivated by the practical requirements of robot path planning, a generalized constrained optimization problem (GCOP) with not only logic AND but also logic OR relationships was proposed and a mathematical solution developed previously. This paper inherits the fundamental ideas of inequality and optimization techniques from the previous work, converts the obstacle avoidance problem into a semi-infinite constrained optimization problem with the help of the mathematical transformation, and proposes a direct path planning approach without Cspace calculation, which is quite different from traditional methods. To show its merits, simulation results in 3D space have been presented.
LanguageEnglish
Pages774-787
Number of pages14
JournalJournal of Computer Science and Technology
Volume20
Issue number6
DOIs
Publication statusPublished - 30 Nov 2005

Fingerprint

Obstacle Avoidance
Collision avoidance
Configuration Space
Robot
Robots
Real-time
Path Planning
Motion planning
Constrained optimization
Constrained Optimization Problem
Semi-infinite Optimization
Logic
Path
Workspace
Shrinking
Optimization Techniques
Polygon
Convert
Collision
Mathematical transformations

Keywords

  • path planning
  • obstacle avoidance
  • autonomous underwater vehicles
  • robotics

Cite this

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abstract = "An important concept proposed in the early stage of robot path planning field is the shrinking of a robot to a point and meanwhile the expanding of obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision-free path for a point robot among the Cspace obstacles. However, the research experiences have shown that the Cspace transformation is very hard when the following situations occur: 1) both the robot and obstacles are not polygons, and 2) the robot is allowed to rotate. This situation gets even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. For this reason, direct path planning approaches without the Cspace transformation is quite useful and expected. Motivated by the practical requirements of robot path planning, a generalized constrained optimization problem (GCOP) with not only logic AND but also logic OR relationships was proposed and a mathematical solution developed previously. This paper inherits the fundamental ideas of inequality and optimization techniques from the previous work, converts the obstacle avoidance problem into a semi-infinite constrained optimization problem with the help of the mathematical transformation, and proposes a direct path planning approach without Cspace calculation, which is quite different from traditional methods. To show its merits, simulation results in 3D space have been presented.",
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A generalized real-time obstacle avoidance method without the cspace calculation. / Wang, Yong-Ji; Cartmell, Matthew; Tao, Qui-Ming; Liu, Han.

In: Journal of Computer Science and Technology, Vol. 20, No. 6, 30.11.2005, p. 774-787.

Research output: Contribution to journalArticle

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