G-RRT*: Goal-oriented sampling-based RRT* path planning Algorithm for mobile robot navigation with improved convergence rate

2021 ◽  
Author(s):  
Sivasankar Ganesan ◽  
Senthil Kumar Natarajan ◽  
Asokan Thondiyath
2021 ◽  
Author(s):  
Abderraouf Maoudj ◽  
Abdelfetah Hentout ◽  
Anders Lyhne Christensen ◽  
Ahmed Kouider

2015 ◽  
Vol 5 (3) ◽  
pp. 189-203 ◽  
Author(s):  
Tharindu Weerakoon ◽  
Kazuo Ishii ◽  
Amir Ali Forough Nassiraei

Abstract Artificial Potential Filed (APF) is the most well-known method that is used in mobile robot path planning, however, the shortcoming is that the local minima. To overcome this issue, we present a deadlock free APF based path planning algorithm for mobile robot navigation. The Proposed-APF (P-APF) algorithm searches the goal point in unknown 2D environments. This method is capable of escaping from deadlock and non-reachability problems of mobile robot navigation. In this method, the effective front-face obstacle information associated with the velocity direction is used to modify the Traditional APF (T-APF) algorithm. This modification solves the deadlock problem that the T-APF algorithm often converges to local minima. The proposed algorithm is explained in details and to show the effectiveness of the proposed approach, the simulation experiments were carried out in the MATLAB environment. Furthermore, the numerical analysis of the proposed approach is given to prove a deadlock free motion of the mobile robot.


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