scholarly journals Synthetic generation of spatial graphs

2018 ◽  
Vol 33 (12) ◽  
pp. 2364-2378 ◽  
Author(s):  
Vicenç Torra ◽  
Annie Jonsson ◽  
Guillermo Navarro-Arribas ◽  
Julián Salas
Keyword(s):  
Spatial Graphs ◽  
Synthetic Generation

Synthetic generation of seasonal precipitation a reply

1971 ◽  
Vol 12 (3) ◽  
pp. 272-273
Author(s):  
L.A.V. Hiemstra ◽  
R.C. Creese
Keyword(s):  
Seasonal Precipitation ◽  
Synthetic Generation

Robot navigation algorithms using learned spatial graphs

Robotica ◽  
1986 ◽  
Vol 4 (2) ◽  
pp. 93-100 ◽  
Author(s):  
S. S. Iyengar ◽  
C. C. Jorgensen ◽  
S. V. N. Rao ◽  
C. R. Weisbin
Keyword(s):  
Robot Navigation ◽  
Sensor Data ◽  
Two Dimensional ◽  
Continuous Transition ◽  
Spatial Graph ◽  
Spatial Graphs ◽  
Navigation Algorithms ◽  
Sensor Information ◽  
Navigation Planning ◽  
Available Information

SUMMARYFinding optimal paths for robot navigation in a known terrain has been studied for some time but, in many important situations, a robot would be required to navigate in completely new or partially explored terrain. We propose a method of robot navigation which requires no pre-learned model, makes maximal use of available information, records and synthesizes information from multiple journeys, and contains concepts of learning that allow for continuous transition from local to global path optimality. The model of the terrain consists of a spatial graph and a Voronoi diagram. Using acquired sensor data, polygonal boundaries containing perceived obstacles shrink to approximate the actual obstacles surfaces, free space for transit is correspondingly enlarged, and additional nodes and edges are recorded based on path intersections and stop points. Navigation planning is gradually accelerated with experience since improved global map information minimizes the need for further sensor data acquisition. Our method currently assumes obstacle locations are unchanging, navigation can be successfully conducted using two-dimensional projections, and sensor information is precise.

Arc index of spatial graphs

2018 ◽  
Vol 90 (3) ◽  
pp. 406-415
Author(s):  
Min Jung Lee ◽  
Sungjong No ◽  
Seungsang Oh
Keyword(s):  
Spatial Graphs ◽  
Arc Index

scholarly journals Yamada Polynomial and Crossing Number of Spatial Graphs

1994 ◽  
Vol 7 (2) ◽  
Author(s):  
Tomoe Motohashi ◽  
Yoshiyuki Ohyama ◽  
K. Taniyama
Keyword(s):  
Crossing Number ◽  
Spatial Graphs
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