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2018-11-09 · 첨삭 강사 Nina

학생이 쓴 원문

Right graph shows the result of estimating force. Y axis is pressing force and x axis is the time frame. Blue dot line means ground truth of interaction force and Red line means estimating force from developed network. From the Graph, Deformable object can infer interaction force from the visual information by using deep learning. However, Robots do not always interact with deformable objects. In the case of interaction with Undeformable object, it is Difficult to predict the interaction force from the image due to less variation of image. Other databases have been generated to show that interaction forces can be predicted when interacting with rigid or deformable objects. Electrical current of motor which is using during the movement of lod is added more to the database for learning. The learning network architecture is more complicated for estimating interaction force during interacting rigid object.

강사 첨삭

Good evening Mr. [이름],
Thank you for sending this in.
I hope I was able to correct it the way you mean it.

Let us discuss more of this in our class.
See you.

Teacher Nina

Right graph shows the result of estimating force.

>> The right graph shows the result of the estimated force.

Y axis is pressing force and x axis is the time frame.

>> Y axis stands for the pressured force and the x axis stands for the time frame.

Blue dot line means ground truth of interaction force and Red line means estimating force from developed network.

>> The blue dot line stands for the ground truth of interaction force. The red line means the estimated force from the developed network.

From the Graph, Deformable object can infer interaction force from the visual information by using deep learning.

>> Based on the graph, Deformable object can infer interaction force from the visual information by using deep learning.

However, Robots do not always interact with deformable objects.

>> correct

In the case of interaction with Undeformable object, it is Difficult to predict the interaction force from the image due to less variation of image

>> In the case of interaction with Undeformable object, it is Difficult to predict the interaction force from the image due to less variation of image.

Other databases have been generated to show that interaction forces can be predicted when interacting with rigid or deformable objects.

>> The other database was generated to show the interaction forces that could be predicted when interacting with rigid or deformable objects.

Electrical current of motor which is using during the movement of lod is added more to the database for learning.

>> The electrical current of motor that was used during the movement of lod was added to the database for learning.

The learning network architecture is more complicated for estimating interaction force during interacting rigid object.

>> The architectural learning network was more complicated in estimating interaction force during the interaction with the rigid object.

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