Online Learning and Teaching of Emergent Behaviors in Multi-Robot Teams

被引:3
|
作者
Costa, Luis Feliphe S. [1 ]
do Nascimento, Tiago P. [2 ]
Goncalves, Luiz Marcos G. [1 ]
机构
[1] Univ Fed Rio Grande do Norte UFRN, Dept Comp & Automat, BR-59064741 Natal, RN, Brazil
[2] Univ Fed Paraiba UFPB, Dept Comp Syst, Syst Engn & Robot Lab LaSER, BR-58051900 Joao Pessoa, Paraiba, Brazil
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Task analysis; Multi-robot systems; Robot sensing systems; Impedance; Education; Programming; Multirobot leaning; behavior-based robotics; knowledge transference; emergent behavior; SLIDING MODE CONTROL;
D O I
10.1109/ACCESS.2019.2951013
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this manuscript, we propose an approach that allows a team of robots to create new (emergent) behaviors at execution time. Basically, we improve the approach called N-Learning used for self-programming of robots in a team, by modifying and extending its functioning structure. The basic capability of behavior sharing is increased by the catching of emergent behaviors at run time. With this, all robots are able not only to share existing knowledge, here represented by blocks of codes containing desired behaviors but also to creating new behaviors as well. Experiments with real robots are presented in order to validate our approach. The experiments demonstrate that after the human-robot interaction with one robot using Program by Demonstration, this robot generates a new behavior at run time and teaches a second robot that performs the same learned behavior through this improved version of the N-learning system.
引用
收藏
页码:158989 / 159001
页数:13
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