Title
Developing Robot Drumming Skill with Listening-Playing Loop.
Abstract
Reacting according to external sounds is an important ability in multi-robot and human-robot collaboration. Although network might be the first choice to connect multi-agents in the robot world, the unexpected connection snap would be a disaster to the whole system. Utilizing sounds is a feasible and supplementary way to transfer information between agents, which is also a smart and robust way to support swarm intelligence. In this paper, under the scenario of a robot band, the issue how each robot member achieves its performance ability is focused. Unlike most of the previous researches, we emphasize that robot's performance ability is achieved all by itself in an autonomous way. And an approach of Listening-Playing Loop (LPL) is proposed, where the developmental learning is involved. With a simple drumming robot, the proposed approach is evaluated. Experimental results show the proposed approach is effective, and via transferring raw audio data to the motion control, the robot successfully develops the drumming ability.
Year
DOI
Venue
2017
10.1007/978-3-319-61833-3_59
ADVANCES IN SWARM INTELLIGENCE, ICSI 2017, PT II
Keywords
Field
DocType
Multi-robot collaboration,Listening-playing loop,Drumming skill acquisition,Cognitive robots,Developmental learning
Developmental learning,Motion control,Computer science,Swarm intelligence,Active listening,Raw audio format,Human–computer interaction,Artificial intelligence,Cognitive robots,Robot,Machine learning
Conference
Volume
ISSN
Citations 
10386
0302-9743
0
PageRank 
References 
Authors
0.34
6
5
Name
Order
Citations
PageRank
Xingfang Wu100.68
Tianlin Liu212.71
Yian Deng301.35
Xihong Wu427953.02
Dingsheng Luo54611.61