DeLellis Pietro, Cadolini Edoardo, Croce Arrigo, Yang Yanpeng, di Bernardo Mario, Porfiri Maurizio
Department of Electrical Electrical Engineering and Information Technology, University of Naples Federico II. Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering.
Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, School of Mechanical Engineering, Tianjin University, Tianjin, China.
IEEE Trans Robot. 2020 Feb;36(1):28-41. doi: 10.1109/tro.2019.2943066. Epub 2019 Sep 23.
The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.
在超过二十五年的时间里,利用受生物启发的机器人来调节活体动物行为的可能性一直吸引着生物学家和工程师的关注。从早期对昆虫的研究到最近对哺乳动物的探索,我们见证了一些引人入胜的应用,这些应用沿着新的方向推动了我们对动物行为的理解。尽管取得了重大进展,但大多数研究都集中在开环控制系统上,在这种系统中,机器人执行预定动作,而不依赖于动物行为。我们将社会行为的数学建模整合到机器人与活体动物交互的现实反馈定律设计中。特别是,我们利用了斑马鱼行为数据驱动建模的最新进展。最终,我们建立了一个新颖的机器人平台,该平台允许对受生物启发的3D打印斑马鱼复制品进行实时驱动,以实现基于模型的动物行为控制。我们通过一系列实验展示了我们的方法,这些实验旨在阐明活体受试者对复制品相对于同种个体的评估,并量化闭环控制的生物学价值。