Time Series Motion Generation Considering Long Short-Term Motion

09/09/2019
by   Kazuki Fujimoto, et al.
0

Various adaptive abilities are required for robots interacting with humans in daily life. It is difficult to design adaptive algorithms manually; however, by using end-to-end machine learning, labor can be saved during the design process. In our previous research, a task requiring force adjustment was achieved through imitation learning that considered position and force information using a four-channel bilateral control. Unfortunately, tasks that include long-term (slow) motion are still challenging. Furthermore, during system identification, there is a method known as the multi-decimation (MD) identification method. It separates lower and higher frequencies, and then identifies the parameters characterized at each frequency. Therefore, we proposed utilizing machine learning to take advantage of the MD method to infer short-term and long-term (high and low frequency, respectively) motion. In this paper, long-term motion tasks such as writing a letter using a pen fixed on a robot are discussed. We found differences in suitable sampling periods between position and force information. The validity of the proposed method was then experimentally verified, showing the importance of long-term inference with adequate sampling periods.

READ FULL TEXT
research
03/16/2022

An Independently Learnable Hierarchical Model for Bilateral Control-Based Imitation Learning Applications

Recently, motion generation by machine learning has been actively resear...
research
03/06/2021

Bilateral Control-Based Imitation Learning for Velocity-Controlled Robot

Machine learning is now playing important role in robotic object manipul...
research
11/12/2020

Motion Generation Using Bilateral Control-Based Imitation Learning with Autoregressive Learning

Robots that can execute various tasks automatically on behalf of humans ...
research
11/03/2022

Convolution channel separation and frequency sub-bands aggregation for music genre classification

In music, short-term features such as pitch and tempo constitute long-te...
research
08/07/2023

Video-based Person Re-identification with Long Short-Term Representation Learning

Video-based person Re-Identification (V-ReID) aims to retrieve specific ...
research
03/11/2021

Imitation learning for variable speed motion generation over multiple actions

Robot motion generation methods using machine learning have been studied...
research
02/26/2019

MRS-VPR: a multi-resolution sampling based global visual place recognition method

Place recognition and loop closure detection are challenging for long-te...

Please sign up or login with your details

Forgot password? Click here to reset