Path Planning for Unmanned Vehicle Motion Based on Road Detection Using Online Road Map and Satellite Image

Author(s):  
Van-Dung Hoang ◽  
Danilo Caceres Hernandez ◽  
Alexander Filonenko ◽  
Kang-Hyun Jo
Author(s):  
Wesley Au ◽  
Chao Chen ◽  
Hoam Chung

The aim of this paper is to define a process to expand the overall reachable workspace of the 5R mechanism and to conduct feasible path planning between configurations within that space, even in cases where the initial and final configurations exist in different modes. It is known that if a mechanism has multiple working modes, there is a unique workspace for each configuration, and they are often only partially connected to each other in a complex manner. Serial singularities allow the mechanism to remain stiff and controllable. These regions are utilised to link disconnected workspaces to maximise the overall reachable workspace to form the global workspace road map. This paper focuses on the 2-DOF path planning of the 5R planar mechanism. A generalised method for analysing complex workspaces of parallel mechanisms is proposed, the rotary disk search for finding the connected reachable workspace, a strategy for global path finding by analysing the global workspace road map and local path generation are discussed.


2021 ◽  
Author(s):  
Kai Zhang ◽  
Luhe Wang ◽  
Jinwen Hu ◽  
Zhao Xu ◽  
Chubing Guo

2011 ◽  
Vol 403-408 ◽  
pp. 1233-1239
Author(s):  
Szu Yu Shen ◽  
Rong Chin Lo

This paper proposes a technique of calling ALV remotely. Firstly, sending the GPS information of the target to the ALV by wireless network, then path planning is completed by prepared map data. If the target is changing in navigation, a new path to the terminal point will be to re-plan. AdaBoost algorithm [1] is introduced for implementingroad detection; different types of classifiers are trained to detect different road surfaces. In conclusion, the ALV is able to determine driving directions on different road surfaces.


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