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A Haptic-Based Proximity Sensing System for Buried Object in Granular Material

Zeqing Zhang, Ruixing Jia, Youcan Yan, Ruihua Han, Shijie Lin, Qian Jiang, Liangjun Zhang, Jia Pan

Abstract

The proximity perception of objects in granular materials is significant, especially for applications like minesweeping. However, due to particles' opacity and complex properties, existing proximity sensors suffer from high costs from sophisticated hardware and high user-cost from unintuitive results. In this paper, we propose a simple yet effective proximity sensing system for underground stuff based on the haptic feedback of the sensor-granules interaction. We study and employ the unique characteristic of particles -- failure wedge zone, and combine the machine learning method -- Gaussian process regression, to identify the force signal changes induced by the proximity of objects, so as to achieve near-field perception. Furthermore, we design a novel trajectory to control the probe searching in granules for a wide range of perception. Also, our proximity sensing system can adaptively determine optimal parameters for robustness operation in different particles. Experiments demonstrate our system can perceive underground objects over 0.5 to 7 cm in advance among various materials.

A Haptic-Based Proximity Sensing System for Buried Object in Granular Material

Abstract

The proximity perception of objects in granular materials is significant, especially for applications like minesweeping. However, due to particles' opacity and complex properties, existing proximity sensors suffer from high costs from sophisticated hardware and high user-cost from unintuitive results. In this paper, we propose a simple yet effective proximity sensing system for underground stuff based on the haptic feedback of the sensor-granules interaction. We study and employ the unique characteristic of particles -- failure wedge zone, and combine the machine learning method -- Gaussian process regression, to identify the force signal changes induced by the proximity of objects, so as to achieve near-field perception. Furthermore, we design a novel trajectory to control the probe searching in granules for a wide range of perception. Also, our proximity sensing system can adaptively determine optimal parameters for robustness operation in different particles. Experiments demonstrate our system can perceive underground objects over 0.5 to 7 cm in advance among various materials.

Paper Structure

This paper contains 13 sections, 24 equations, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Problem Statement
  4. Physical Principle
  5. Sensor Design
  6. Prototype
  7. Motion Control
  8. Haptic-Based Proximity Sensing
  9. Generalization to Various GMs
  10. Experiment Results
  11. Proximity Sensing in Sands
  12. Proximity Sensing in Various GMs
  13. Conclusion

Figures (6)

  • Figure 1: Prototype of our haptic-based proximity sensing system, GRAINS, for the near-field perception of the buried object in granules.
  • Figure 2: Physical principle. (a) Failure wedge zone ahead of the probe as it moves in granules. (b)-(d) State changes of the failure wedge zone as the probe approaches the object in GMs and (e) the corresponding force variations. Inset: force chains (from peters2005characterization) when the granule jamming occurs.
  • Figure 3: Definition of the spiral trajectory. Enlarged view: one circular motion in the spiral trajectory, i.e., $\theta \in [0, 2\pi]$.
  • Figure 4: Snapshots of the failure wedge zone ahead of the probe along (a) linear and (b) spiral trajectories.
  • Figure 5: Proximity sensing experiments in sands. (a),(e) Baseline method. (b)-(d),(f) Our mehtod.
  • ...and 1 more figures

Theorems & Definitions (2)

  • definition 1
  • definition 2