Towards Deep Learning Based Robot Automatic Choreography System

Ruiqi Wu, Wenyao Peng, Changle Zhou, Fei Chao*, Longzhi Yang, Chih Min Lin, Changjing Shang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


It is a challenge task to enable a robot to dance according to different types of music. However, two problems have not been well resolved yet: (1) how to assign a dance to a certain type of music, and (2) how to ensure a dancing robot to keep in balance. To tackle these challenges, a robot automatic choreography system based on the deep learning technology is introduced in this paper. First, two deep learning neural network models are built to convert local and global features of music to corresponding features of dance, respectively. Then, an action graph is built based on the collected dance segments; the main function of the action graph is to generate a complete dance sequence based on the dance features generated by the two deep learning models. Finally, the generated dance sequence is performed by a humanoid robot. The experimental results shows that, according to the input music, the proposed model can successfully generate dance sequences that match the input music; also, the robot can maintain its balance while it is dancing. In addition, compared with the dance sequences in the training dataset, the dance sequences generated by the model has reached the level of artificial choreography in both diversity and innovation. Therefore, this method provides a promising solution for robotic choreography automation and design assistance.

Original languageEnglish
Title of host publicationIntelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings
EditorsHaibin Yu, Jinguo Liu, Lianqing Liu, Yuwang Liu, Zhaojie Ju, Dalin Zhou
Number of pages12
ISBN (Print)9783030275372
Publication statusPublished - 1 Jan 2019
Event12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 - Shenyang, China
Duration: 8 Aug 201911 Aug 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11743 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Intelligent Robotics and Applications, ICIRA 2019


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