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Centre of Mass Estimation of Grasped Objects Using Cost Effective Sensors

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Robot Intelligence Technology and Applications 7 (RiTA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 642))

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Abstract

Tactile sensing systems are often not commercially available, very costly, or the processes involved in making them are not easily copied by those without substantial resources [5]. A cost effective alternative to the tactile and torque based sensors used in previous centre of mass (CoM) estimation literature is investigated. The core aim of the paper is to design an alternative to higher cost tactile sensors. The final prototype uses three force sensitive resistors in a triangular arrangement, capable of measuring both the magnitude and direction of the force applied to the sensor as a whole. Due to noise in the data and the number of data-points collected a suitable CoM estimation model was not able to be built. Despite this, the paper presents a low-cost sensor prototype (totalling less than £15), which is capable of detecting small changes in the direction and magnitude of the force applied to the gripper. It is a useful alternative to more expensive tactile sensors with further investigation.

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Authors and Affiliations

  1. Department of Computer Science, University of York, York, YO10 5DD, UK

    Thomas Emmerson & Pengcheng Liu

Authors
  1. Thomas Emmerson
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  2. Pengcheng Liu
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Corresponding author

Correspondence to Pengcheng Liu .

Editor information

Editors and Affiliations

  1. School of Information and Communication Technology, Griffith University, Southport, Australia

    Jun Jo

  2. Department of Aerospace Engineering, KAIST, Daejeon, Korea (Republic of)

    Han-Lim Choi

  3. School of Information and Communication Technology, Griffith University, Southport, Australia

    Marde Helbig

  4. Department of Mechanical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Korea (Republic of)

    Hyondong Oh

  5. Department of Mechanical Engineering, KAIST, Daejeon, Korea (Republic of)

    Jemin Hwangbo

  6. Department of Mechanical Engineering, KAIST, Daejeon, Korea (Republic of)

    Chang-Hun Lee

  7. School of Information and Communication Technology, Griffith University, Southport, Australia

    Bela Stantic

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Emmerson, T., Liu, P. (2023). Centre of Mass Estimation of Grasped Objects Using Cost Effective Sensors. In: Jo, J., et al. Robot Intelligence Technology and Applications 7. RiTA 2022. Lecture Notes in Networks and Systems, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-031-26889-2_15

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