In view of the shortcomings of low search efficiency and many path turning points of Probabilistic Roadmaps (PRM), a bidirectional search PRM global path planning algorithm is proposed. The algorithm improves the search connection rules by using the positive and negative directions to search the path alternately, so that the connection of unnecessary nodes reduces, thereby speeding up the efficiency of path planning. Besides, the algorithm incorporates cubic spline interpolation. That will increase the smoothness of path planning and ensure that the mobile robot can realize the path planning task more smoothly and safely. The simulation results show that the improved algorithm can effectively improve the convergence speed and path smoothnes...
Path planning is a fundamental problem in mobile robots that optimize the path to determine how the ...
The artificial potential field method is used in mobile robot path planning extensively because of i...
Aiming at the problems of low success rate and slow learning speed of the DDPG algorithm in path pla...
In this paper, we propose a new path planning algorithm based on the probabilistic roadmaps method (...
In order to solve the problems of A* algorithm in raster map path planning, such as large memory con...
Abstract—Robot path planning problem is one of most impor-tant task mobile robots. This paper propos...
© 2019 St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences. A...
Path planning is a very important step for mobile smart vehicles in complex environments. Sampling b...
Path planning plays a key role in the application of mobile robots and it is an important way to ach...
In the field of artificial intelligence and mobile robotics, calculating suitable paths, for point t...
Global path planning of mobile robot aims to provide a safe and smooth path for mobile robot navigat...
Global path planning is the key technology of mobile robot outdoor work,and global path planning alg...
A based on Rapidly-exploring Random Tree(RRT) and Particle Swarm Optimizer (PSO) for path planning o...
Among the shortcomings of the A* algorithm, for example, there are many search nodes in path plannin...
The Probabilistic RoadMap planner (PRM) has been applied with success to multiple planning problems ...
Path planning is a fundamental problem in mobile robots that optimize the path to determine how the ...
The artificial potential field method is used in mobile robot path planning extensively because of i...
Aiming at the problems of low success rate and slow learning speed of the DDPG algorithm in path pla...
In this paper, we propose a new path planning algorithm based on the probabilistic roadmaps method (...
In order to solve the problems of A* algorithm in raster map path planning, such as large memory con...
Abstract—Robot path planning problem is one of most impor-tant task mobile robots. This paper propos...
© 2019 St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences. A...
Path planning is a very important step for mobile smart vehicles in complex environments. Sampling b...
Path planning plays a key role in the application of mobile robots and it is an important way to ach...
In the field of artificial intelligence and mobile robotics, calculating suitable paths, for point t...
Global path planning of mobile robot aims to provide a safe and smooth path for mobile robot navigat...
Global path planning is the key technology of mobile robot outdoor work,and global path planning alg...
A based on Rapidly-exploring Random Tree(RRT) and Particle Swarm Optimizer (PSO) for path planning o...
Among the shortcomings of the A* algorithm, for example, there are many search nodes in path plannin...
The Probabilistic RoadMap planner (PRM) has been applied with success to multiple planning problems ...
Path planning is a fundamental problem in mobile robots that optimize the path to determine how the ...
The artificial potential field method is used in mobile robot path planning extensively because of i...
Aiming at the problems of low success rate and slow learning speed of the DDPG algorithm in path pla...