Optimal Path Planning of an Autonomous Mobile Robot Using Genetic Algorithm

2012 ◽  
Vol 488-489 ◽  
pp. 1747-1751
Author(s):  
V. Vasu ◽  
K. Jyothi Kumar
Keyword(s):  
Mobile Robot ◽  
Hardware Implementation ◽  
Robot Navigation ◽  
Fitness Function ◽  
Optimal Path ◽  
Autonomous Mobile Robot ◽  
Software Simulation ◽  
Optimal Path Planning ◽  
The Past ◽  
Extract Information

An autonomous Mobile Robot (AMR) is a machine able to extract information from its environment and move in a meaningful and purposeful manner. Robot Navigation and Obstacle avoidance are the most important problems in mobile robots. In the past, a number of soft computing algorithms have been designed by many researchers for robot navigation problems but very few are actually implementable because they haven’t considered robot size as parameter. This paper presents software simulation and hardware implementation of navigation of a mobile robot avoiding obstacles and selecting optimal path in a static environment using evolution based Genetic algorithms with robot size as a parameter in fitness function.

scholarly journals PSO based path planner of an autonomous mobile robot

2012 ◽  
Vol 2 (2) ◽  
Author(s):  
B. Deepak ◽  
Dayal Parhi
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Fitness Function ◽  
Optimal Path ◽  
Mobile Robot Navigation ◽  
Autonomous Mobile Robot ◽  
Swarm Optimization ◽  
Novel Approach ◽  
Fitness Value ◽  
Path Planner

AbstractA novel approach based on particle swarm optimization has been presented in this paper for solving mobile robot navigation task. The proposed technique tries to optimize the path generated by an intelligent mobile robot from its source position to destination position in its work space. For solving this problem, a new fitness function has been modelled, which satisfies the obstacle avoidance and optimal path traversal conditions. From the obtained fitness values of each particle in the swarm, the robot moves towards the particle which is having optimal fitness value. Simulation results are provided to validate the feasibility of the developed methodology in various unknown environments.

A New Real Time Path Planning for Mobile Robot Navigation Using Invasive Weed Optimization Algorithm

2014 ◽  
Author(s):  
Prases K. Mohanty ◽  
Dayal R. Parhi
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Robot Navigation ◽  
Fitness Function ◽  
Optimal Path ◽  
Mobile Robot Navigation ◽  
Invasive Weed Optimization ◽  
Invasive Weed ◽  
Planning Algorithm ◽  
Path Planner

In this article a new optimal path planner for mobile robot navigation based on invasive weed optimization (IWO) algorithm has been addressed. This ecologically inspired algorithm is based on the colonizing property of weeds and distribution. A new fitness function has been formed between robot to goal and obstacles, which satisfied the conditions of both obstacle avoidance and target seeking behavior in robot present in the environment. Depending on the fitness function value of each weed in the colony the robot that avoids obstacles and navigating towards goal. The optimal path is generated with this developed algorithm when the robot reaches its destination. The effectiveness, feasibility, and robustness of the proposed navigational algorithm has been performed through a series of simulation and experimental results. The results obtained from the proposed algorithm has been also compared with other intelligent algorithms (Bacteria foraging algorithm and Genetic algorithm) to show the adaptability of the developed navigational method. Finally, it has been concluded that the proposed path planning algorithm can be effectively implemented in any kind of complex environments.

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