Nonholonomic path planning optimization for Dubins' vehicles

2011 ◽  
Author(s):  
Douglas G. Macharet ◽  
Armando Alves Neto ◽  
Vilar F. da Camara Neto ◽  
Mario F. M. Campos
Keyword(s):  
Path Planning ◽  
Planning Optimization ◽  
Dubins Vehicles

A joint global and local path planning optimization for UAV task scheduling towards crowd air monitoring

2021 ◽  
Vol 193 ◽  
pp. 107913
Author(s):  
Yuan Tang ◽  
Yiming Miao ◽  
Ahmed Barnawi ◽  
Bander Alzahrani ◽  
Reem Alotaibi ◽  
...  
Keyword(s):  
Path Planning ◽  
Task Scheduling ◽  
Air Monitoring ◽  
Local Path Planning ◽  
Planning Optimization ◽  
Local Path ◽  
Global And Local

Path Planning Optimization in SDN Using Machine Learning Techniques

2021 ◽  
Author(s):  
Marlon Rodriguez ◽  
Ricardo Flores Moyano ◽  
Noel Perez ◽  
Daniel Riofrio ◽  
Diego Benitez
Keyword(s):  
Machine Learning ◽  
Path Planning ◽  
Machine Learning Techniques ◽  
Planning Optimization ◽  
Learning Techniques

Research on Path Planning Optimization of Intelligent Robot in Warehouse Fire Fighting Scene

2021 ◽  
pp. 41-51
Author(s):  
Qingshui Xue ◽  
Zongyang Hou ◽  
Haifeng Ma ◽  
Xingzhong Ju ◽  
Haozhi Zhu ◽  
...  
Keyword(s):  
Path Planning ◽  
Fire Fighting ◽  
Intelligent Robot ◽  
Planning Optimization ◽  
Warehouse Fire

scholarly journals Stochastic C-GNet Environment Modeling and Path Planning Optimization in a Narrow and Long Space

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Jianjian Yang ◽  
Zhiwei Tang ◽  
Xiaolin Wang ◽  
Zirui Wang ◽  
Biaojun Yin ◽  
...  
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Three Dimensional ◽  
Test Model ◽  
Environment Modeling ◽  
Grid Network ◽  
Planning Optimization ◽  
Elevation Data ◽  
Dynamic Stochastic ◽  
Terrain Elevation

This study proposes a novel method of optimal path planning in stochastic constraint network scenarios. We present a dynamic stochastic grid network model containing semienclosed narrow and long constraint information according to the unstructured environment of an underground or mine tunnel. This novel environment modeling (stochastic constraint grid network) computes the most likely global path in terms of a defined minimum traffic cost for a roadheader in such unstructured environments. Designing high-dimensional constraint vector and traffic cost in nodes and arcs based on two- and three-dimensional terrain elevation data in a grid network, this study considers the walking and space constraints of a roadheader to construct the network topology for the traffic cost value weights. The improved algorithm of variation self-adapting particle swarm optimization is proposed to optimize the regional path. The experimental results both in the simulation and in the actual test model settings illustrate the performance of the described approach, where a hybrid, centralized-distributed modeling method with path planning capabilities is used.

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