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 Path Planning of Mobile Robot in Unknown Environment

2010 ◽  
pp. 122-127
Author(s):  
Pradipta kumar Das ◽  
Romesh Laishram ◽  
Amit Konar
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Cost Function ◽  
Shortest Path ◽  
Target Position ◽  
Initial Position ◽  
A Algorithm ◽  
Unknown Environment ◽  
Feasible Path ◽  
The Cost

In this paper, we study the online path planning for khepera II mobile robot in an unknown environment. The well known heuristic A* 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. The proposed path finding strategy is designed in a grid-map form of an unknown environment with static unknown obstacles. 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 and time metric as the cost function.

World representation and path planning for a mobile robot

Robotica ◽  
1988 ◽  
Vol 6 (1) ◽  
pp. 35-40 ◽  
Author(s):  
E. Palma-Villalon ◽  
P. Dauchez
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Cost Function ◽  
Experimental Results ◽  
Spatial Relationships ◽  
Simple Representation ◽  
Matrix Description ◽  
Path Planner ◽  
The Cost

SUMMARYThis paper is related to the problem of navigation of a mobile robot amidst obstacles. In order to easily take into account any modification of the environment, we propose a very simple representation of the obstacles, based on the use of rectangles, as well as a matrix description of the spatial relationships between the obstacles. We also present a path planner based on a A* algorithm, the features of which are specifically designed for our world of rectangles. The cost function takes into account both the length of the path and the number of turns. Some experimental results and implementation details are also given in this paper.

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.  

An Integrated Algorithm for Autonomous Navigation of a Mobile Robot in an Unknown Environment

2008 ◽  
Vol 12 (4) ◽  
pp. 328-335 ◽  
Author(s):  
Lee Gim Hee ◽  
◽  
Marcelo H. Ang Jr. ◽  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Hybrid Method ◽  
Autonomous Navigation ◽  
Prior Information ◽  
Optimal Path ◽  
Unknown Environment ◽  
Global Path Planning ◽  
Local Navigation ◽  
Navigation Algorithms

Global path planning algorithms are good in planning an optimal path in a known environment, but would fail in an unknown environment and when reacting to dynamic and unforeseen obstacles. Conversely, local navigation algorithms perform well in reacting to dynamic and unforeseen obstacles but are susceptible to local minima failures. A hybrid integration of both the global path planning and local navigation algorithms would allow a mobile robot to find an optimal path and react to any dynamic and unforeseen obstacles during an operation. However, the hybrid method requires the robot to possess full or partial prior information of the environment for path planning and would fail in a totally unknown environment. The integrated algorithm proposed and implemented in this paper incorporates an autonomous exploration technique into the hybrid method. The algorithm gives a mobile robot the ability to plan an optimal path and does online collision avoidance in a totally unknown environment.

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