Detecting a Sphere Object with an Array of Magnetic Sensors

Byungmun Kang, Dae Eun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we developed an inventive magnetic field sensing system using an array of magnetic sensors inspired by animals using a huge natural Earth’s magnetic filed such as pigeons and red foxes. Inspired by their biological behaviors and the animals’ compassion-like sensory nerves, a magnetic field sensing system was constructed using eight magnetic sensors. This is not a simple combination of sensors, but rather a circular arrangement of eight analog magnetic sensors with a DC solenoid in the middle. So, this system can measure the signal from both the solenoid’s signal and the surrounding magnetic object simultaneously. Through this functions, we can find a global direction of the sensing system and estimate the direction of the magnetic object around the system. We also used a method of locating a metal sphere, which was inspired by the way a sand scorpion estimates its prey. Applying this to the system, it is the purpose of this paper to estimate the direction of its objects using changes in magnetic fields caused by magnetic object.

Original languageEnglish
Title of host publicationFrom Animals to Animats 15 - 15th International Conference on Simulation of Adaptive Behavior, SAB 2018, Proceedings
EditorsPoramate Manoonpong, Jørgen Christian Larsen, Xiaofeng Xiong, John Hallam, Jochen Triesch
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783319976273
Publication statusPublished - 2018
Event15th International Conference on the Simulation of Adaptive Behavior, SAB 2018 - Frankfurt/Main, Germany
Duration: 2018 Aug 142018 Aug 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10994 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on the Simulation of Adaptive Behavior, SAB 2018

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2017R1A2B4011455).

Publisher Copyright:
© 2018, Springer Nature Switzerland AG.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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