scholarly journals A dynamic path planning method for wheeled mobile robots (Dyna-bug).

2017 ◽  
Vol 7 (3) ◽  
pp. 123-128
Author(s):  
Suat Karakaya ◽  
Gurkan Kucukyildiz ◽  
Hasan Ocak
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Cost Function ◽  
Sensor Data ◽  
Stationary Condition ◽  
Wheeled Mobile Robots ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
The Cost ◽  
Local Map

Abstract   In this study, a hybrid path-planning scheme is presented. The main contribution of this paper is merging the static grid costs of the global map and the immediate environmental structure of the local map. The stationary condition of the map and the instant local goal is weighted by certain coefficients in order to determine the next move of the wheeled mobile robot (WMR). Thus, the cost function is defined in terms of the grid costs and the dynamic parameters. The main assumption is that the WMR on which this scheme is executed must be equipped with a field scanning sensor. The sensor readings in each processing cycle are pre-processed before plugging in the cost function. The passages in the local map are extracted from the sensor data, then the optimal collision-free point lying on the passages is obtained via the cost function. Keywords: Path planning, collision avoidance, mobile robot.  

scholarly journals D* lite algorithm based path planning of mobile robot in static Environment

2012 ◽  
pp. 286-290
Author(s):  
Pradipta kumar Das ◽  
S .N. Patro ◽  
C. N. Panda ◽  
Bunil Balabantaray
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Cost Function ◽  
Shortest Path ◽  
Target Position ◽  
Initial Position ◽  
Distance Metric ◽  
Unknown Environment ◽  
Feasible Path ◽  
The Cost

In this paper, we study the path planning for khepera II mobile robot in an unknown environment. The well known heuristic D* lite algorithm is implemented to make the mobile robot navigate through static obstacles and find the shortest path from an initial position to a target position by avoiding the obstacles. and to perform efficient re-planning during exploration. The proposed path finding strategy is designed in a grid-map form of an unknown environment with static unknown obstacles. The robot moves within the unknown environment by sensing and avoiding the obstacles coming across its way towards the target. When the mission is executed, it is necessary to plan an optimal or feasible path for itself avoiding obstructions in its way and minimizing a cost such as time, energy, and distance. In our study we have considered the distance metric as the cost function.

scholarly journals A Novel GRU-RNN Network Model for Dynamic Path Planning of Mobile Robot

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 15140-15151 ◽  
Author(s):  
Jianya Yuan ◽  
Hongjian Wang ◽  
Changjian Lin ◽  
Dawei Liu ◽  
Dan Yu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Network Model ◽  
Dynamic Path Planning ◽  
Dynamic Path

Path Planning for Mobile Robot Based on Improved Ant Colony Algorithm

2013 ◽  
Vol 385-386 ◽  
pp. 717-720 ◽  
Author(s):  
Rui Wang ◽  
Zai Tang Wang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Ant Colony Algorithm ◽  
Probability Function ◽  
Ant Colony ◽  
Local Optimum ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
Improved Ant Colony Algorithm ◽  
Improved Algorithm

This paper presents a dynamic path planning method based on improved ant colony algorithm. In order to increasing the algorithm’s convergence speed and avoiding to fall into local optimum, we propose adaptive migratory probability function and updating the pheromone. We apply the improved algorithm to path planning for mobile robot and the simulation experiment proved that improved algorithm is viable and efficient.

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