Study of Virtual Nasopharyngeal Navigation Based on Virtual Endoscopy Technology

2016 ◽  
Vol 28 ◽  
pp. 44-52
Author(s):  
Lei Guo ◽  
Wei Zhang ◽  
Lei Zhao ◽  
Ming Hu ◽  
Gui Zhi Xu
Keyword(s):  
Path Planning ◽  
Rapid Development ◽  
Virtual Endoscopy ◽  
Medical Image Segmentation ◽  
Mr Images ◽  
3D Image Reconstruction ◽  
Extraction Algorithm ◽  
Planning Algorithm ◽  
Center Path ◽  
Path Planning Algorithm

With the rapid development of medical imaging technology, computer graphics and visualization technologies, virtual endoscopy technology emerged. It mainly includes 2D medical image segmentation, 3D image reconstruction, path planning and virtual roaming. However, the path planning of virtual endoscopy has become one of the obstacles in this field due to the high irregularity of the nasopharyngeal anatomy structure. In this study, the nasopharynx including meatus nasi, pharyngeal canal, maxillary sinus, frontal sinus, sphenoid sinus, and ethmoid sinus is segmented and 3D reconstructed using MR images. The key technology of virtual endoscopy - center path planning algorithm is implemented based on distance transform. Also, two improved algorithms of center path planning are proposed. One is the selection algorithm of branch path and the other is the extraction algorithm for complex path based on human-computer interaction. These two improved algorithms can not only allow the traditional path planning algorithm to handle multiple branching structure but make roaming path to start at any point. Our experimental results satisfied the needs of clinical practice.

scholarly journals Human-Machine Cooperation and Path Planning for Complex Road Conditions

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Guanghong Zhou
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Industrial Robot ◽  
Rapid Development ◽  
Industrial Robots ◽  
Path Optimization ◽  
Planning System ◽  
Target Point ◽  
Planning Algorithm ◽  
Path Planning Algorithm

With the rapid development of the information age, the development of industrial robots is also advancing by leaps and bounds. In the scenes of automobile, medicine, aerospace, and public service, we have fully enjoyed the convenience brought by industrial robots. However, with the continuous development of industrial robot-related concepts and technologies, human-computer interaction and cooperation have become the development trend of industrial robot. In this paper, the human-machine cooperation and path optimization of industrial robot in a complex road environment are studied and analyzed. At the theoretical modeling level, firstly, the industrial robot is modeled and obstacle avoidance is analyzed based on the kinematics of industrial robot; thus, an efficient and concise collision detection model of industrial robot is proposed. At the algorithm level, in view of the complex road conditions faced by industrial robots, this paper will study and analyze the obstacle avoidance strategy of human-computer cooperation and real-time path optimization algorithm of industrial robots. Based on the virtual target point algorithm, this paper further improves the problem that the goal of the traditional path planning algorithm cannot be fully covered, so as to propose the corresponding improved path planning algorithm of industrial robots. In the experimental part, based on the existing industrial robot system, the human-machine cooperation and path planning system proposed in this paper are designed. The experimental results show that the algorithm proposed in this paper improves the accuracy of obstacle avoidance by about 10 points and the corresponding convergence speed by about 5% compared with the traditional algorithm and the experimental effect is remarkable.

Research on Path Planning Method for On-Line Measurement of Blisk

2014 ◽  
Vol 577 ◽  
pp. 677-680
Author(s):  
Lei Zhang ◽  
Qiang Yuan ◽  
Qing Zhou Sun ◽  
Yu Song ◽  
Ji Zhao
Keyword(s):  
Path Planning ◽  
B Spline ◽  
Feature Point Extraction ◽  
Line Measurement ◽  
Extraction Algorithm ◽  
Planning Algorithm ◽  
On Line ◽  
The Cost ◽  
Path Planning Algorithm ◽  
Measurement Area

The blisk is an important component of aviation engine and its level of machining and measurement will directly affect the application properties of the engine. This paper investigates the on-line measurement of single blade of the blisk. The section lines and the points to be measured are determined by using the empirical formula based on B-spline theory and feature point extraction algorithm. The probe-blade interference problem is solved by dividing the measurement area into different sectors and the posture angle of the probe in different inference-free sector domain is determined. The CATIA simulation is conducted to validate the correctness of the path planning algorithm for measurement. The measuring path planning plays an important role in improving the efficiency and reducing the cost of measurement.

scholarly journals A 2D Optimal Path Planning Algorithm for Autonomous Underwater Vehicle Driving in Unknown Underwater Canyons

2021 ◽  
Vol 9 (3) ◽  
pp. 252
Author(s):  
Yushan Sun ◽  
Xiaokun Luo ◽  
Xiangrui Ran ◽  
Guocheng Zhang
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Underwater Vehicles ◽  
Optimal Path ◽  
Small Scale ◽  
Target Point ◽  
Safe Driving ◽  
Policy Gradient ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This research aims to solve the safe navigation problem of autonomous underwater vehicles (AUVs) in deep ocean, which is a complex and changeable environment with various mountains. When an AUV reaches the deep sea navigation, it encounters many underwater canyons, and the hard valley walls threaten its safety seriously. To solve the problem on the safe driving of AUV in underwater canyons and address the potential of AUV autonomous obstacle avoidance in uncertain environments, an improved AUV path planning algorithm based on the deep deterministic policy gradient (DDPG) algorithm is proposed in this work. This method refers to an end-to-end path planning algorithm that optimizes the strategy directly. It takes sensor information as input and driving speed and yaw angle as outputs. The path planning algorithm can reach the predetermined target point while avoiding large-scale static obstacles, such as valley walls in the simulated underwater canyon environment, as well as sudden small-scale dynamic obstacles, such as marine life and other vehicles. In addition, this research aims at the multi-objective structure of the obstacle avoidance of path planning, modularized reward function design, and combined artificial potential field method to set continuous rewards. This research also proposes a new algorithm called deep SumTree-deterministic policy gradient algorithm (SumTree-DDPG), which improves the random storage and extraction strategy of DDPG algorithm experience samples. According to the importance of the experience samples, the samples are classified and stored in combination with the SumTree structure, high-quality samples are extracted continuously, and SumTree-DDPG algorithm finally improves the speed of the convergence model. Finally, this research uses Python language to write an underwater canyon simulation environment and builds a deep reinforcement learning simulation platform on a high-performance computer to conduct simulation learning training for AUV. Data simulation verified that the proposed path planning method can guide the under-actuated underwater robot to navigate to the target without colliding with any obstacles. In comparison with the DDPG algorithm, the stability, training’s total reward, and robustness of the improved Sumtree-DDPG algorithm planner in this study are better.

Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation

2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Traffic Condition ◽  
Planning Time ◽  
Dynamic Path Planning ◽  
Short Period ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm ◽  
Chaos Genetic Algorithm

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

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