OSCAR: A Low-Cost, Open-Source Robotic Platform Design for Cognitive Research

被引：1
|
作者：
Fallas-Hernandez, Emanuel [1 ]
Baldares, Ronald J. L. [1 ]
Luis Crespo, Juan [1 ]
机构：
[1] Costa Rica Inst Technol, Mechatron Engn Dept, LIANA, Lab Artificial Intelligence Nat Sci, Cartago, Costa Rica
来源：
2021 3RD IEEE INTERNATIONAL CONFERENCE ON BIOINSPIRED PROCESSING (BIP): A CLEI COSTA RICA 2021 EVENT | 2021年
关键词：
Robot design; cognitive architecture; task learning; visual perception;
D O I：
10.1109/BIP53678.2021.9612905
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Research in cognitive robotics has been traditionally carried out in high-end research robots. This poses a barrier to many research institutions that cannot handle the costs associated with purchasing and operating this type of robot. In this paper, the design of a low-cost and open-source robot called OSCAR is presented. This robot was purposely designed to adapt to manipulation tasks in the context of cognitive robotics. The morphology, sensors equipped and software architecture of the robot are explained. Moreover, an initial implementation based in the Gazebo simulator is used to carry out an experiment involving a manipulation task using the Multilevel Darwinist Brain cognitive architecture. Results show that OSCAR is capable of learning a task and to obtain general information of its environment when paired with a cognitive architecture.
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页数：6
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