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2021 Fiscal Year Research-status Report

Development of a Distributed Stretchable 3-axis Sensing System

Research Project

Project/Area Number 21K14131
Research InstitutionWaseda University

Principal Investigator

トモ ティト・プラドノ  早稲田大学, 次世代ロボット研究機構, 次席研究員(研究院講師) (00844193)

Project Period (FY) 2021-04-01 – 2023-03-31
Keywordsstretchable / 3-axis / tactile sensor
Outline of Annual Research Achievements

In FY2021, we developed the prototype of a distributed, stretchable, 3-axis soft skin sensor, "Stretch uSkin". The sensor's working principle is based on Hall-Effect sensing, where the force can be detected by displacing a small permanent magnet embedded inside the silicone structure floating above MLX90393, a 3D magnetometer chip. However, instead of using a rigid Printed Circuit Board (PCB), we also use stretchable PCBs that were manufactured by Cir-tech and Connectec Japan. These PCBs are made of a stretchable substrate where the wires are stretchable silver pastes with a meander pattern.
Several experiments such as measuring bus resistances due to stretching cycle, distance, and speed were conducted to analyze the performance of each PCB design.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

Even though the sensor can measure distributed 3-axis force, the maximum stretch is limited to only up to 150% of its original length. It is challenging to cover robot joints with this stretch ratio.
We also found that the bus resistance of one out of two sensor models becomes very high after stretching it more than 50 cycles. Both sensors had corrupted output data, possibly because of the unreliable I2C communication due to this problem. It is impractical considering that robots usually will operate on the order of a million times.
In FY2022, we initially plan to cover robot joints with sensors from FY2021 and evaluate their performance. Because of these problems, we must develop another version of a stretchable tactile sensor using a different approach before we can install it on a robot.

Strategy for Future Research Activity

In FY2022, we will develop the second version of a stretchable skin sensor. The sensor will use coil wires instead of stretchable silver pastes with a meander pattern. Our target is not only to achieve a stretch ratio of more than 300% but also can provide reliable output.
We will conduct several experiments similar to what we did in FY2021 to evaluate the sensor's characteristics.
Finally, we will use the sensor to cover robot joints. For example, Allegro Hand or Nicebot.

Causes of Carryover

1. To purchase raw materials and equipment for manufacturing stretch PCB in-house and also conducting experiments. For example, copper wires, silicone rubber, 3D printer materials, reference sensor, etc.
2. To manufacture rigid PCBs with magnetometers (MLX90393) and microcontrollers
3. To purchase tools for documentation such as a camera and PC

  • Research Products

    (4 results)

All 2022 2021

All Journal Article (1 results) Presentation (3 results)

  • [Journal Article] A Robotic Grasping State Perception Framework with Multi-Phase Tactile Information and Ensemble Learning2022

    • Author(s)
      Yan Gang、Schmitz Alexander、Funabashi Satoshi、Somlor Sophon、Tomo Tito Pradhono、Sugano Shigeki
    • Journal Title

      IEEE Robotics and Automation Letters

      Volume: - Pages: 1~1

    • DOI

      10.1109/LRA.2022.3151260

  • [Presentation] Detection of Slip from Vision and Touch2022

    • Author(s)
      Yan, G., Schmitz, A., Tomo, T. P., Somlor, S., Funabashi, S., Sugano, S.
    • Organizer
      IEEE International Conference on Robotics and Automation( 国際学会)
  • [Presentation] “Safe Skin” - A Low-Cost Capacitive Proximity-Force-Fusion Sensor For Safety in Robots2021

    • Author(s)
      Wang, Z., Gao, H., Schmitz, A., Somlor, S., Tomo, T.P., Sugano, S.
    • Organizer
      IEEE/RSJ International Conference on Intelligent Robots and Systems( 国際学会)
  • [Presentation] SCT-CNN: A Spatio-Channel-Temporal Attention CNN for Grasp Stability Prediction2021

    • Author(s)
      Yan, G., Schmitz, A., Funabashi, S., Somlor, S., Tomo, T.P., Sugano, S.
    • Organizer
      IEEE International Conference on Robotics and Automation( 国際学会)

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Published: 2022-12-28  

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