scholarly journals Level set and Fat Fast Marching Method for normal and dynamic path planning of pursuit-evasion problem

Author(s):  
Cheng-Yuan Wu ◽  
Jing-Sin Liu
IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 41367-41378 ◽  
Author(s):  
Zengfu Wang ◽  
Qing Wang ◽  
Bill Moran ◽  
Moshe Zukerman

Author(s):  
S. Garrido ◽  
L. Moreno

This chapter presents a new sensor-based path planner, which gives a fast local or global motion plan capable to incorporate new obstacles data. Within the first step, the safest areas in the environment are extracted by means of a Voronoi Diagram. Within the second step, the fast marching method is applied to the Voronoi extracted areas so as to get the trail. This strategy combines map-based and sensor-based designing operations to supply a reliable motion plan, whereas it operates at the frequency of the sensor. The most interesting characteristics are high speed and reliability, as the map dimensions are reduced to a virtually one-dimensional map and this map represents the safest areas within the environment.


Author(s):  
Minal M. Purani ◽  
Shobha Krishnan

Technology is proliferating. Many methods are used for medical imaging .The important methods used here are fast marching and level set in comparison with the watershed transform .Since watershed algorithm was applied to an image has over clusters in segmentation . Both methods are applied to segment the medical images. First, fast marching method is used to extract the rough contours. Then level set method is utilized to finely tune the initial boundary. Moreover, Traditional fast marching method was modified by the use of watershed transform. The method is feasible in medical imaging and deserves further research. It could be used to segment the white matter, brain tumor and other small and simple structured organs in CT and MR images. In the future, we will integrate level set method with statistical shape analysis to make it applicable to more kinds of medical images and have better robustness to noise.


2019 ◽  
Vol 34 (7) ◽  
pp. 6-17
Author(s):  
Santiago Garrido ◽  
David Alvarez ◽  
Fernando Martin ◽  
Luis Moreno

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