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Cognitive response navigation algorithm for mobile robots using biological antennas

Published online by Cambridge University Press:  03 December 2013

Jiliang Jiang ,
Dawei Tu ,
Shuo Xu  and
Qijie Zhao
Jiliang Jiang
Affiliation:
School of Mechatronic Engineering and Automation, and Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai 200072, China
Dawei Tu*
Affiliation:
School of Mechatronic Engineering and Automation, and Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai 200072, China
Shuo Xu
Affiliation:
School of Mechatronic Engineering and Automation, and Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai 200072, China
Qijie Zhao
Affiliation:
School of Mechatronic Engineering and Automation, and Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai 200072, China
*
*Corresponding author. E-mail: tdwshu@staff.shu.edu.cn
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Summary

We present BioBug, a bionic cognitive response navigation algorithm for mobile robots based on neuroethology principles. It includes a biological antenna model for environment perception and an improved Bug algorithm for motion planning and control. The biological antenna model delineates the interested sensing areas, and thus decreases the computational burden. Then, this obtained environment stimulation is responded to generate the corresponding walking behavior according to BioBug. Simulations and experiments have been carried out in different conditions of obstacle density and boundary shape through algorithm comparisons. Compared with the competitors, BioBug is characterized by not only a smaller path length, but also shorter time for obstacle escape. The results demonstrate the practicality, environment robustness, and obstacle avoidance efficiency of the algorithm.

Keywords

Bug algorithmAutonomous navigationMobile robotBiological antennaCognitionBionics

Information

Type
Articles
Information
Robotica , Volume 32 , Issue 5 , August 2014 , pp. 743 - 756
Copyright
Copyright © Cambridge University Press 2013 

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