A hybrid path planning system combining the A*-method and RBF-networks

1997 ◽  
pp. 793-798 ◽  
Author(s):  
Thomas Frontzek ◽  
Nils Goerke ◽  
Rolf Eckmiller
Keyword(s):  
Path Planning ◽  
Planning System ◽  
Rbf Networks

UAS Mission Path Planning System (MPPS) Using Hybrid-Game Coupled to Multi-Objective Optimiser

2009 ◽  
Author(s):  
DongSeop Lee ◽  
Jacques Periaux ◽  
Luis Felipe Gonzalez
Keyword(s):  
Path Planning ◽  
Computational Cost ◽  
Optimization Techniques ◽  
Planning System ◽  
Unmanned Aerial Systems ◽  
Three Dimension ◽  
Design Quality ◽  
Nsga Ii ◽  
Start Position ◽  
Multi Objective

This paper presents the application of advanced optimization techniques to Unmanned Aerial Systems (UAS) Mission Path Planning System (MPPS) using Multi-Objective Evolutionary Algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA Non-dominated Sorting Genetic Algorithms II (NSGA-II) and a Hybrid Game strategy are implemented to produce a set of optimal collision-free trajectories in three-dimensional environment. The resulting trajectories on a three-dimension terrain are collision-free and are represented by using Be´zier spline curves from start position to target and then target to start position or different position with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a Hybrid-Game strategy to a MOEA and for a MPPS.

Design of the Autonomous Path Planning System for Mining Robots Based on Stereo Vision

2021 ◽  
pp. 596-605
Author(s):  
Youge Su ◽  
Wanghui Bu ◽  
Jing Chen ◽  
Sihang Li ◽  
Mingzhi Liu
Keyword(s):  
Path Planning ◽  
Stereo Vision ◽  
Planning System

Trajectory planning for lab robots based on global vision and Voronoi roadmaps

Robotica ◽  
2005 ◽  
Vol 23 (4) ◽  
pp. 467-477 ◽  
Author(s):  
Waldir L. Roque ◽  
Dionísio Doering
Keyword(s):  
Path Planning ◽  
Trajectory Planning ◽  
Planning System ◽  
Global Vision ◽  
Navigation Control ◽  
Feasible Path ◽  
Robot Configurations

This paper discusses the techniques and their applications in the development of a path planning system composed of three modules, namely: global vision (GVM), trajectory planning (TPM) and navigation control (NCM). The GVM captures and processes the workspace image to identify the obstacle and the robot configurations. These configurations are used by the TPM to generate the Voronoi roadmap, to compute the maximal clearance shortest feasible path and the visibility pathway between two configurations. The NCM controls the robot functionalities and navigation. To validate the path planning system, three sets of experiments have been conducted using the Lab robot Khepera, which have shown very good results.

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