A Global Path Planning Approach based on Improved A * Algorithm for Intelligent Vessel Navigating

2021 ◽  
Author(s):  
Meifang Liu ◽  
Junsheng Ren
Keyword(s):  
Path Planning ◽  
A Algorithm ◽  
Global Path Planning ◽  
Planning Approach

Offline decoupled path planning approach for effective coordination of multiple robots

Robotica ◽  
2009 ◽  
Vol 28 (4) ◽  
pp. 477-491 ◽  
Author(s):  
Shital S. Chiddarwar ◽  
N. Ramesh Babu
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Minimum Distance ◽  
Degrees Of Freedom ◽  
Multiple Robots ◽  
A Algorithm ◽  
Two Phase ◽  
Six Degrees Of Freedom ◽  
Planning Approach ◽  
End Effectors

SUMMARYIn this paper, a decoupled offline path planning approach for determining the collision-free path of end effectors of multiple robots involved in coordinated manipulation is proposed. The proposed approach for decoupled path planning is a two-phase approach in which the path for coordinated manipulation is generated with a coupled interaction between collision checking and path planning techniques. Collision checking is done by modelling the links and environment of robot using swept sphere volume technique and utilizing minimum distance heuristic for interference check. While determining the path of the end effector of robots involved in coordinated manipulation, the obstacles present in the workspace are considered as static obstacles and the links of the robots are viewed as dynamic obstacles by the other robot. Coordination is done in offline mode by implementing replanning strategy which adopts incremental A* algorithm for searching the collision-free path. The effectiveness of proposed decoupled approach is demonstrated by considering two examples having multiple six degrees of freedom robots operating in 3D work cell environment with certain static obstacles.

scholarly journals An A*-based Bacterial Foraging Optimisation Algorithm for Global Path Planning of Unmanned Surface Vehicles

2020 ◽  
Vol 73 (6) ◽  
pp. 1247-1262
Author(s):  
Yang Long ◽  
Zheming Zuo ◽  
Yixin Su ◽  
Jie Li ◽  
Huajun Zhang
Keyword(s):  
Sensitivity Analysis ◽  
Path Planning ◽  
Optimal Parameter ◽  
A Algorithm ◽  
Unmanned Surface Vehicles ◽  
Parameter Combination ◽  
Bacterial Foraging ◽  
Optimisation Algorithm ◽  
Global Path Planning ◽  
Influential Parameters

The bacterial foraging optimisation (BFO) algorithm is a commonly adopted bio-inspired optimisation algorithm. However, BFO is not a proper choice in coping with continuous global path planning in the context of unmanned surface vehicles (USVs). In this paper, a grid partition-based BFO algorithm, named AS-BFO, is proposed to address this issue in which the enhancement is contributed by the involvement of the A* algorithm. The chemotaxis operation is redesigned in AS-BFO. Through repeated simulations, the relative optimal parameter combination of the proposed algorithm is obtained and the most influential parameters are identified by sensitivity analysis. The performance of AS-BFO is evaluated via five size grid maps and the results show that AS-BFO has advantages in USV global path planning.

A Novel Path Planning Approach with Bidirectional A* Algorithm Based on Road Characteristics

2021 ◽  
Author(s):  
Weihua Li ◽  
Bowen Chen ◽  
Pengpeng Li ◽  
Xuewen Geng ◽  
Jianfeng Wang
Keyword(s):  
Path Planning ◽  
A Algorithm ◽  
Planning Approach ◽  
Road Characteristics

Robotic Fish Path Planning Based on an Improved A* Algorithm

2013 ◽  
Vol 336-338 ◽  
pp. 968-972 ◽  
Author(s):  
Huan Wang ◽  
Yu Lian Jiang
Keyword(s):  
Path Planning ◽  
Complex Environment ◽  
A Algorithm ◽  
Global Path Planning ◽  
Local Path Planning ◽  
Search Data ◽  
Infinite Loop ◽  
Transition Points ◽  
Local Path ◽  
Divide And Rule

Applying the global path planning to traditional A* algorithm in a complex environment and a lot of obstacles will result in an infinite loop because there are too many search data. To resolve this problem, this paper provides a new divide-and-rule path planning method which is based on improved A* algorithm. It uses several transition points to divide the entire grid map areas into several sub-regions. We set different speeds in each sub-region for local path planning. Thus the complex global path planning is turned into some simple local path planning. It reduces the search data of A* algorithm and avoids falling into the infinite loop. By this method, this paper designs the path planning of heading the ball, and smoothes the orbit. The simulation results show that the improved A* algorithm is better and more effective than the traditional one.

A path planning approach based on multi-direction A* algorithm for ships navigating within wind farm waters

2019 ◽  
Vol 184 ◽  
pp. 311-322 ◽  
Author(s):  
Lei Xie ◽  
Shuangfei Xue ◽  
Jinfen Zhang ◽  
Mingyang Zhang ◽  
Wuliu Tian ◽  
...  
Keyword(s):  
Path Planning ◽  
Wind Farm ◽  
A Algorithm ◽  
Planning Approach
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