Design and Summary Analysis Draft 4

 

MEC 1281

Summary_Analysis

By Chin Yong Sheng

8th April 2021

According to the article, "Soft robotic arm..." (2020), researchers from MIT constructed a soft robot that is capable of estimating its 3D configuration through its skin that is covered with sensors. However, the sensors and neural network still lack refinement to accurately capture subtle and dynamic motions.  

Matheson mentioned that there are two advantages the soft robot has over traditional rigid robots. Due to its soft body, it has the ability to move in infinite number of ways at any time. Secondly, it does not rely on motion-capture cameras to provide feedback regarding 3D movement and positions. Instead, it relies on its own sensors. Matheson quotes one of the researchers Dr Truby, who states that "The sensors can be fabricated using off-the shelf materials"(Matheson,2020). Dr.Truby also commented that the sensors are easy to fabricate, meaning any lab would be able to construct their owns sensor. Dr.Truby also highlighted that the materials used for constructing the sensor should possess "piezoresistive" properties. The material's resistance varies according to the motion. The change in resistance affects voltage output linearly. The resulting voltage output will then be relayed to the robot.

However, the robots ability to move without restriction results in increased difficulty to use it in "control" applications. To alleviate this problem, researchers from MIT commented that new robots have to undergo deep learning. Doing so, the robot will progressively be more effective in capturing meaningful feedback signals. Researchers from MIT aim to explore more feasible options such as utilizing better sensors and to provide better deep learning methods to reduce training time.

 While the soft robotic arm is more suitable than traditional robot in real-life scenarios, technology has yet to be refined. Matheson quotes Daniela Rus, who states that “ Think of your own body: You can close your eyes and reconstruct the world based on feedback from your skin,”(Matheson,2020). Future soft robot should be dexterous and capable of manipulating objects in its surrounding through better sensors and deep learning. In order to achieve this, better materials and sensors which are more sophisticated should be used.

Incorporating a better material for future prototypes should be investigated as the initial material used is not ideal. The material used couldn't stretch much without making cuts on the material itself. In the article "Advanced carbon materials...", (Zhang.Y & Jian.M, 2017), states that carbon materials such as carbon nanomaterial and graphene are strong contenders for this particular application. It is said that these two materials can be easily assembled into multi-scaled macroscopic structures, resulting in good flexibility and conductivity. The article further states that carbon materials can be prepared through different approaches, thus creating even more room for future development. 

Secondly, an improvement to the deep learning method would be desirable. In the article, "The SLAM Problem...", a process called Simultaneous Localisation and Mapping (SLAM) is used to map environment using a machine's sensors. The article also mentioned that the process is incapable of mapping a dynamically changing environment due to uncertainties. In the article written by Denim.F, Nemra.A, Louadj.K(2016), Filters are added to the sensor to counteract this undesirable behaviour. A filter known as Smooth Variable Structure Filter(SVSF) is used to provide a better estimate to the uncertainties and errors captured by the sensors. The graph shown in figure 6 illustrates how the filter works. Through estimation of the errors, the filter changes the estimated trajectory consistently. Through filtering, the estimated trajectory is shown to be very close to the system's true trajectory. By adding filters to the soft robotic arms, it helps the robot to capture the environment accurately.

In the article, "Soft robotic arm..." (Matheson,2020), Dr.Truby mentioned:" As hypothesized, the sensors did capture the trunk's general movement, but it was really noisy". Substituting the original sensor material for carbon-based material will be a great improvement in "noise" reduction, thus resolving the "noise" issue. Additionally, adding filters to the sensor helps to filter out uncertainties in signals captured by the sensor. This enables the sensors to be more accurate.

 References:

Denim, F., Nemra, A. & Louadj, K.(2016). Robust SVSF-SLAM For Unmanned Vehicle In Unknown Environment. Science Direct, 49(21), 386-394.

https://www.sciencedirect.com/science/article/pii/S2405896316321760?via%3Dihub

 Joseph, A., Yvan, P., Joaquim, S. & Xavier, L. (2008). The SLAM Problem: A Survey. 

http://eia.udg.es/~qsalvi/papers/2008-CCIAa.pdf

Matheson,R.(2020, February 16). Soft Robotic Arms Uses Flexible Sensors To Understand Its Position. Control Engineering.

 https://www.controleng.com/articles/soft-robotic-arm-uses-flexible-sensors-to-understand-its-position/

Zhang, Y., & Jian, .M. (2017, Sep 1). Advanced Carbon Materials For Flexible And Wearable Sensors. Science China Materials, 60(11), 1026-1062.  

https://engine.scichina.com/publisher/scp/journal/SCMs/60/11/10.1007/s40843-017-9077-x?slug=fulltext

Comments

  1. Brad Blackstone6 April 2021 at 18:27

    Thanks for the revision, Mark. There are still problems with various citation conventions and the second item on your reference list.

    ReplyDelete

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