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Trajectory Planning and the Target Search by the Mobile Robot in an Environment Using a Behavior-Based Neural Network Approach

Published online by Cambridge University Press:  14 November 2019

Krishna Kant Pandey Open the ORCID record for Krishna Kant Pandey [Opens in a new window]  and
Dayal R. Parhi
Krishna Kant Pandey*
Affiliation:
Mechanical Engineering Department, National Institute of Technology, Rourkela, India
Dayal R. Parhi
Affiliation:
Mechanical Engineering Department, National Institute of Technology, Rourkela, India
*
*Corresponding author. E-mail: kknitrkl@yahoo.in
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Summary

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Navigation and path analysis in a cluttered environment is a challenging task over the last few decades. In this paper, a behavior-based neural network (BNN) and reactive control architecture have been presented for navigation of the mobile robot. Two different reactive behaviors have been taken as inputs function. Obstacle position is the first reactive behavior given by u(o), whereas obstacle angle u(n) according to the target position is the second reactive behavior. The angular velocity and steering angle are the output of the controller. The backpropagation architecture reduces the errors of weight function and records the best weight data that match the BNN controller. Using the BNN algorithm, the robot reacts quickly as compared to other developed techniques. To validate the performance of the controller, simulation and experimental results have been compared in the common platforms. The deviation in results for both the scenarios is found to be within 10%. The results of the BNN algorithm have also been compared with other existing techniques. Effectiveness of the proposed technique is measured in terms of smoothness of the realistic path, collision point detection, path length, and performance time.

Keywords

Behavior-based neural network (BNN)NavigationPath planningObstacle avoidanceRobot localization.
Type
Articles
Information
Robotica , Volume 38 , Issue 9 , September 2020 , pp. 1627 - 1641
Copyright
© Cambridge University Press 2019

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