Optimized NURBS Curve and Surface Modelling Using Simulated Evolution Algorithm

Zhang, Jing; Feng, Shui; Hanguo, Cui

doi:10.1109/wcse.2009.847

Search citation statements

Order By: Relevance

Paper Sections

Select...

Theoretical Background1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2015

Publication Types

Select...

Book2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, finding a correct parameterization and the weight of the control points when calculating the curve have been the main issues in curve fitting techniques. Many evolutionary optimization techniques have been successfully applied [10,11]. Through this paper, we aim to exploit the effect of the weight parameter.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

NURBS Based Multi-objective Path Planning

Jalel¹,

Marthon²,

Hamouda³

2015

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Path planning presents a key question for an autonomous robot to evolve in its environment. Hence, it has been largely dealt in recent years. Actually, finding feasible paths and optimizing them for different objectives is computationally difficult. In this context, this paper introduces a new mobile robot path planning algorithm by introducing an optimized NURBS (Non Uniform Rational B-Spline) curve modelling using Genetic Algorithm to represent the generated path from the specified start location to the desired goal. Thus, given an a priori knowledge of the environment, an accurate fitness function is used to compute a curvature-constrained and obstacles-avoiding smooth path, with minimum length and low variations of curvature. The performance of the proposed algorithm is demonstrated through extensive MATLAB simulation studies.

show abstract

Section: Theoretical Backgroundmentioning

confidence: 99%