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Time-variant artificial potential field (TAPF): a breakthrough in power-optimized motion planning of autonomous space mobile robots

Published online by Cambridge University Press:  15 August 2014

Matin Macktoobian  and
Mahdi Aliyari Shoorehdeli
Matin Macktoobian*
Affiliation:
Fault Detection and Identification Lab (FDI), Electrical and Computer Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran
Mahdi Aliyari Shoorehdeli
Affiliation:
Fault Detection and Identification Lab (FDI), Electrical and Computer Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran
*
*Corresponding author. E-mail: matinking@hotmail.com
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Summary

In this paper, a novel scheme is presented to conquer the motion-planning problem for autonomous space robots. Minimizing the consumed energy of atomic batteries within the daily planetary missions of robot on the planet is taken into account, i.e., utilization of the generated solar power by its embedded photocells leads to saving energy of batteries for night missions. Aforementioned objective could be acquired by appropriate interaction of motion planning paradigm with shadows of obstacles. Modeling of the shadow with the proposed artificial potential field leads to generalize the concept of potential fields not only for static and dynamic obstacles but also for being confronted with the intrinsic time-variant phenomena such as shadows. With due attention to the noticeable computational complexity of the introduced strategy, fuzzy techniques are applied to optimize the sampling times effectively. To accomplish this objective, a smart control scheme based on the fuzzy logic is mounted to the primitive version of algorithm. Regarding the need to identify some structural parameters of obstacles, PIONEER™ mobile robot is designed as a test bed for the verification of simulated results. Investigation on empirical accomplishments shows that the goal-oriented definition of Time–Variant Artificial Potential Fields is able to resolve the motion-planning problem in planetary applications.

Keywords

Artificial potential fieldMotion planningMobile robotNavigationSpace Robotics
Type
Articles
Information
Robotica , Volume 34 , Issue 5: RAAD , May 2016 , pp. 1128 - 1150
Copyright
Copyright © Cambridge University Press 2014 

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