Adaptive GA-based Potential Field Algorithm for Collision-free Path Planning of Mobile Robots in Dynamic Environments

2018 ◽  
Author(s):  
Saeed Bakhshi Germi ◽  
Mohammad A. Khosravi ◽  
Rasul FesharakiFard
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Free Path ◽  
Potential Field ◽  
Dynamic Environments

scholarly journals Learning Innovative Routes for Mobile Robots in Dynamic Partially Unknown Environments

10.5772/5787 ◽  
2005 ◽  
Vol 2 (3) ◽  
pp. 21
Author(s):  
Kristo Heero ◽  
Alvo Aabloo ◽  
Maarja Kruusmaa
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Shortest Path ◽  
Dynamic Environments ◽  
Distance Transform ◽  
Test Results ◽  
Approach To Learning ◽  
Planning Strategy ◽  
Unknown Environments ◽  
Planning Strategies

This paper examines path planning strategies in partially unknown dynamic environemnts and introduces an approach to learning innovative routes. The approach is verified against shortest path planning with a distance transform algorithm, local and global replanning and suboptimal route following in unknown, partially unknown, static and dynamic environments. We show that the learned routes are more reliable and when traversed repeatedly the robot's behaviour becomes more predictable. The test results also suggest that the robot's behaviour depends on knowledge about the environemnt but not about the path planning strategy used.

Metrology-aware Path Planning for Agricultural Mobile Robots in Dynamic Environments

2021 ◽  
Author(s):  
R. A. Saeed ◽  
Giacomo Tomasi ◽  
Ganesh Govindarajan ◽  
Renato Vidoni ◽  
Karl D. Von Ellenrieder
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Dynamic Environments
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