Obstacle Avoidance Behaviors for Mobile Robots Using Genetic Algorithms and Recurrent Neural Networks

Savage, Jesús; Muñoz, Stalin; Matamoros, Mauricio; Osorio, Roman

doi:10.3182/20130911-3-br-3021.00100

Cited by 11 publications

(8 citation statements)

References 5 publications

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“…Savage et al [293] also presented a strategy combining GA with recurrent neural network (RNN) to address path planning problem. GA was used to find the obstacle avoidance behavior and then implemented in RNN to control the robot.…”

Section: Other Hybrid Path Planningmentioning

confidence: 99%

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.

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Section: Other Hybrid Path Planningmentioning

confidence: 99%

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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“…θ is the process of x position, y position of the robot change and the process of robot turning respectively. So, this is a model in terms of mapping control on to states, "Based on the limitations of equations (1), (2) and (3) [9], unicycle model has been used", which successfully overcome the wheel velocities problem. Then, translational velocity (v), that is speed and angular velocity ( ω ) has been considered instead of considering wheel velocities.…”

Section: Design Approachmentioning

confidence: 99%

“…Means, it assist in everywhere where people needs. Now, to follow someone robot needs a special kind of behaviors [1] that give it the ability to avoid an obstacle and reach its goal [2]- [3]. Avoid obstacle robot can be humanoid or can be mobile.…”

Section: Introductionmentioning

confidence: 99%

Low Cost Obstacle Avoidance Robot with Logic Gates and Gate Delay Calculations

Ahad¹

2018

ACIS

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As a fast growing field, robots are greatly used to achieve the desired task more accurately and mitigate the difficulties in odd environments where human face immense difficulties. In this paper an obstacle avoidance robot has been designed using basic gates. It can detect the obstacle and directs itself with the help of five sensors. When sensor detects an obstacle it gives the pulse high and vice-versa. A differential drive model has been chosen, which has two wheels and a cluster wheel. Left and right motor are used as a physical machine and it will be controlled by logic; K-map has been used to do it. Basic gates help to execute the equation of motors as well as to make robot faster, precise and efficient. To make more comprehensible comparative time delay estimation has been added in this paper.

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“…They have analyzed the working efficiency for wild data sets. Savage et al (2013) have designed a genetic algorithm (GA)-based approach for navigational analysis of a mobile robot. Ming et al (1996) have described about a fuzzy logic controller hybridized with GA in a biped robot.…”

Section: Introductionmentioning

confidence: 99%

Path optimization for navigation of a humanoid robot using hybridized fuzzy-genetic algorithm

Rath

Parhi

Das

et al. 2019

IJIUS

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Purpose Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical interventions. As a result, navigation and path planning has emerged as one of the most promising area of research for humanoid models. In this paper, a fuzzy logic controller hybridized with genetic algorithm (GA) has been proposed for path planning of a humanoid robot to avoid obstacles present in a cluttered environment and reach the target location successfully. The paper aims to discuss these issues. Design/methodology/approach Here, sensor outputs for nearest obstacle distances and bearing angle of the humanoid are first fed as inputs to the fuzzy logic controller, and first turning angle (TA) is obtained as an intermediate output. In the second step, the first TA derived from the fuzzy logic controller is again supplied to the GA controller along with other inputs and second TA is obtained as the final output. The developed hybrid controller has been tested in a V-REP simulation platform, and the simulation results are verified in an experimental setup. Findings By implementation of the proposed hybrid controller, the humanoid has reached its defined target position successfully by avoiding the obstacles present in the arena both in simulation and experimental platforms. The results obtained from simulation and experimental platforms are compared in terms of path length and time taken with each other, and close agreements have been observed with minimal percentage of errors. Originality/value Humanoids are considered more efficient than their wheeled robotic forms by their ability to mimic human behavior. The current research deals with the development of a novel hybrid controller considering fuzzy logic and GA for navigational analysis of a humanoid robot. The developed control scheme has been tested in both simulation and real-time environments and proper agreements have been found between the results obtained from them. The proposed approach can also be applied to other humanoid forms and the technique can serve as a pioneer art in humanoid navigation.

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Obstacle Avoidance Behaviors for Mobile Robots Using Genetic Algorithms and Recurrent Neural Networks

Cited by 11 publications

References 5 publications

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Low Cost Obstacle Avoidance Robot with Logic Gates and Gate Delay Calculations

Path optimization for navigation of a humanoid robot using hybridized fuzzy-genetic algorithm

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