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      A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots

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          Abstract

          Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the “hit and run” technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes.

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          Most cited references36

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          Rolling in Nature and Robotics: A Review

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            A Closed-Form Formula for Magnetic Dipole Localization by Measurement of Its Magnetic Field and Spatial Gradients

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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                28 May 2017
                June 2017
                : 17
                : 6
                : 1231
                Affiliations
                Engineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, Singapore 487372, Singapore; fang_wu@ 123456sutd.edu.sg (F.W.); akash.roboticist@ 123456gmail.com (A.V.); sohgimsong@ 123456sutd.edu.sg (G.S.S.); kristinwood@ 123456sutd.edu.sg (K.L.W.)
                Author notes
                [* ]Correspondence: foongshaohui@ 123456sutd.edu.sg ; Tel.: +65-6303-6670
                Article
                sensors-17-01231
                10.3390/s17061231
                5492687
                28555030
                e6a894a1-2a31-421c-ae00-747606361aee
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 April 2017
                : 24 May 2017
                Categories
                Article

                Biomedical engineering
                obstacle detection,obstacle avoidance,spherical robot,magnet assembly,miniature robot,sensor optimization

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