Dynamic Graph-Search Algorithm for Global Path Planning in Presence of Hazardous Weather

Author(s):  
M. Garcia ◽  
A. Viguria ◽  
A. Ollero
2020 ◽  
Vol 10 (21) ◽  
pp. 7846
Author(s):  
Hyejeong Ryu

An efficient, hierarchical, two-dimensional (2D) path-planning method for large complex environments is presented in this paper. For mobile robots moving in 2D environments, conventional path-planning algorithms employ single-layered maps; the proposed approach engages in hierarchical inter- and intra-regional searches. A navigable graph of an environment is constructed using segmented local grid maps and safe junction nodes. An inter-regional path is obtained using the navigable graph and a graph-search algorithm. A skeletonization-informed rapidly exploring random tree* (SIRRT*) efficiently computes converged intra-regional paths for each map segment. The sampling process of the proposed hierarchical path-planning algorithm is locally conducted only in the start and goal regions, whereas the conventional path-planning should process the sampling over the entire environment. The entire path from the start position to the goal position can be achieved more quickly and more robustly using the hierarchical approach than the conventional single-layered method. The performance of the hierarchical path-planning is analyzed using a publicly available benchmark environment.


2006 ◽  
Vol 3 (9) ◽  
pp. 453-488 ◽  
Author(s):  
Wen-Ying Chang ◽  
Fei-Bin Hsiao ◽  
Donglong Sheu

Author(s):  
Muhammad Saleem Sumbal

Automatic path planning is one of the most challenging problems confronted by autonomous robots. Generating optimal paths for autonomous robots are some of the heavily studied subjects in mobile robotics applications. This paper documents the implementation of a path planning project using a mobile robot in a structured environment. The environment is detected through a camera and then a roadmap of the environment is built using some algorithms. Finally a graph search algorithm called A* is implemented that searches through the roadmap and finds an optimal path for robot to move from start position to goal position avoiding obstacles


2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.


Author(s):  
Sam Anand ◽  
Mohamed Sabri

Abstract Robots play an important role in the modern factory and are used in a manufacturing cell for several functions such as assembly, material handling, robotic welding, etc. One of the principal problems faced by robots while performing their tasks is the presence of obstacles such as fixtures, tools, and objects in the robot workspace. Such objects could result in a collision with one of the arms of the robots. Fast collision-free motion planning algorithms are therefore necessary for robotic manipulators to operate in a wide variety of changing environments. The configuration space approach is one of the widely used methods for collision-free robotic path planning. This paper presents a novel graph-based method of searching the configuration space for a collision-free path in a robotic assembly operation. Dijkstra’s graph search algorithm is used for optimizing the joint displacements of the robot while performing the assembly task. The methodology is illustrated using a simple robotic assembly planning task.


Sign in / Sign up

Export Citation Format

Share Document