Design of active sensing smart skin for incipient slip detection in robotic applications
Abstract/Contents
- Abstract
- Tactile sensing is paramount for robots operating in human-centered environments to help in understanding interaction with objects. To enable robots to have sophisticated tactile sensing capability, researchers have developed different kinds of tactile sensors for robotic hands to realize the 'sense of touch'. In this study, we are focused on the incipient slip detection problem for robots which is known as one of the most challenging issues in robotic tactile sensing. Currently, most of the slip detection sensors are passive sensors which provide limited information about the sensing parameters. Therefore, this will usually require large amount of data and extra computation effort in accurately classifying slip conditions of robotic hands. Other sensing mechanisms such as optical approaches which can provide enriched sensing parameters for slip detection often suffer from complex sensor configurations and being inflexible in terms of customization. Active sensing, on the other hand, has the advantage of simple sensor configurations, and in the meantime can provide more sensing parameters which will improve the overall efficiency of the tactile sensing capabilities for incipient slip detection. In this thesis, by using the active sensing method, a novel active sensing smart skin technique is developed for incipient slip detection which leverages piezoelectric transducers as actuators/sensors. With this method, a robotic fingertip with the embedded actuator and sensor were created in which the actuator generates ultrasonic guided waves received by the sensor during a slip scenario. By analyzing the received signal using an attenuation-based method, we can monitor the entire contact area evolution during a slip scenario. Therefore, this method can serve as an excellent indicator for early slip detection with the advantage of accurately monitoring the contact condition. In addition, the frustrated total internal reflection method was used to validate the signal attenuation increases with the growing of the contact area. Built on these results, a unique robotic skin was then designed and fabricated which demonstrated robust and sensitive response for incipient slip detection. Finally, an LED slip alert system on a real gripper was developed to demonstrate the capability of our method to be applicable to real robotic finger situations.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Liu, Cheng |
|---|---|
| Degree supervisor | Chang, Fu-Kuo |
| Degree supervisor | Cutkosky, Mark R |
| Thesis advisor | Chang, Fu-Kuo |
| Thesis advisor | Cutkosky, Mark R |
| Thesis advisor | Senesky, Debbie |
| Degree committee member | Senesky, Debbie |
| Associated with | Stanford University, Department of Mechanical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Cheng Liu. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/zn070qt1437 |
Access conditions
- Copyright
- © 2021 by Cheng Liu
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