Research and application of photovoltaic cell online monitoring system for animal robot stimulator_Journal of Biomedical Engineering

Authors：

SHI Yong ¹ , YU Zhihao ² , YAN Rui ¹ , WANG Hui ¹ , YANG Junqing ¹ ,  HUAI Ruituo ¹

1. College of Electrical and Automation Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266510, P. R. China;
2. College of Energy Storage Technology, Shandong University of Science and Technology, Qingdao, Shandong 266510, P. R. China;

Corresponding author：

HUAI Ruituo, Email: huairuituo@163.com

Keywords：

Animal robot; Photovoltaic cell; Online monitoring system

DOI：

10.7507/1001-5515.202109020

Video：

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Power supply plays a key role in ensuring animal robots to obtain effective stimulation. To extending the stimulating time, there is a need to apply photovoltaic cells and monitor their parameter variations, which can help operators to obtain the optimal stimulation strategy. In this paper, an online monitoring system of photovoltaic cells for animal robot stimulators was presented. It was composed of battery information sampling circuit, multi-channel neural signal generator, power module and human-computer interaction interface. When the signal generator was working, remote navigation control of animal robot could be achieved, and the battery voltage, current, temperature and electricity information was collected through the battery information sampling circuit and displayed on the human-computer interaction system in real time. If there was any abnormal status, alarm would be activated. The battery parameters were obtained by charging and discharging test. The battery life under different light intensity and the stimulation effect of neural signal generator were tested. Results showed that the sampling errors of battery voltage, current and electric quantity were less than 15 mV, 5 mA and 6 mAh, respectively. Compared with the system without photovoltaic cells, the battery life was extended by 148% at the light intensity of 78 320 lx, solving the battery life problem to some extent. When animal robot was stimulated with this system, left and right turns could be controlled to complete with the success rate more than 80%. It will help researchers to optimize animal robot control strategies through the parameters obtained in this system.

Citation： SHI Yong, YU Zhihao, YAN Rui, WANG Hui, YANG Junqing, HUAI Ruituo. Research and application of photovoltaic cell online monitoring system for animal robot stimulator. Journal of Biomedical Engineering, 2022, 39(5): 974-981, 990. doi: 10.7507/1001-5515.202109020 Copy

1.	彭勇, 韩晓晓, 王婷婷, 等. 一种用于鲤鱼机器人的光刺激装置及光控实验方法. 生物医学工程学杂志, 2018, 35(5): 720-726.
2.	槐瑞托, 苏学成, 杨俊卿. 动物机器人遥操作导航控制方法. 应用基础与工程科学学报, 2010, 18(2): 352-358.
3.	Gao Z H, Shi Q, Fukuda T, et al. An overview of biomimetic robots with animal behaviors. Neurocomputing, 2019, 332: 339-350.
4.	Brown S. Stealth sharks to patrol the high seas. The New Scientist, 2006, 189(2541): 30-31.
5.	Lehmkuhle M J, Vetter R J, Parikh H, et al. Implantable neural interfaces for characterizing population responses to odorants and electrical stimuli in the nurse shark, Ginglymostoma cirratum. Chem Senses, 2006, 31: A14.
6.	Hirotaka S. Remote radio control of insect flight. Front Integr Neurosci, 2009, 3: 24.
7.	Nobutaka K, Letters M. Artificial control of swimming in goldfish by brain stimulation: confirmation of the midbrain nuclei as the swimming center. Neurosci Lett, 2009, 452(1): 42-46.
8.	Seo J, Choi J, Park S. Wireless navigation of pigeons using polyme r-based fully implantable stimulator: a pilot study using depth electrodes// 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Jeju: IEEE, 2017: 917-920.
9.	卞文超, 苏学成. 放飞世界首只机器人鸟. 大众日报, 2007-03-02.
10.	王勇, 苏学成, 槐瑞托, 等. 动物机器人遥控导航系统. 机器人, 2006, 28(2): 183-186.
11.	王勇, 槐瑞托, 王敏, 等. 基于脑微刺激的智能动物的研究. 中国生物医学工程学报, 2006, 25(4): 497-502..
12.	张韶岷, 王鹏, 江君, 等. 大鼠遥控导航及其行为训练系统的研究. 中国生物医学工程学报, 2007, 26(6): 830-836.
13.	谢合瑞, 郭策, 戴振东. 恒流多通道动物机器人遥控刺激系统的研制. 现代电子技术, 2009, 32(4): 68-71.
14.	陈臣. 应用于昆虫的无线微型刺激系统关键技术的研究. 杭州: 杭州电子科技大学, 2017.
15.	彭勇, 王婷婷, 闫艳红, 等. 鲤鱼机器人无线遥控系统设计与应用. 中国生物医学工程学报, 2019, 38(4): 431-437.
16.	Zhou Z, Liu D, Sun H. Pigeon robot for navigation guided by remote control: System construction and functional verification. J Bionic Eng, 2021, 18(1): 184-196.
17.	李演明, 陈忠会, 杨晓冰, 等. 一种用于低速电动汽车的锂电池管理系统研究. 电力电子技术, 2018, 52(12): 61-64.
18.	Yang P, Yu H Y, Yan Y G. Implementation of the li-ion battery management system based on DS2438. Appl Mech Mater, 2015, 733: 714-717.
19.	曲成树. 安防机器人磷酸铁锂电池管理系统研制. 成都: 电子科技大学, 2019.
20.	Zheng L, Zhu J, Wang G. Novel methods for estimating lithium-ion battery state of energy and maximum available energy. Appl Energ, 2016, 178: 1-8.
21.	He C. Power tracking and state-of-energy balancing of an energy storage system by distributed control. IEEE Access, 2020, 8: 170261-170270.
22.	苏学成, 槐瑞托, 杨俊卿, 等. 控制动物机器人运动行为的脑机制和控制方法. 中国科学: 信息科学, 2012, 42(9): 1130-1146.
23.	王文波, 戴振东. 动物机器人的研究现状与发展. 机械制造与自动化, 2010, 39(2): 1-7.

1. 彭勇, 韩晓晓, 王婷婷, 等. 一种用于鲤鱼机器人的光刺激装置及光控实验方法. 生物医学工程学杂志, 2018, 35(5): 720-726.
2. 槐瑞托, 苏学成, 杨俊卿. 动物机器人遥操作导航控制方法. 应用基础与工程科学学报, 2010, 18(2): 352-358.
3. Gao Z H, Shi Q, Fukuda T, et al. An overview of biomimetic robots with animal behaviors. Neurocomputing, 2019, 332: 339-350.
4. Brown S. Stealth sharks to patrol the high seas. The New Scientist, 2006, 189(2541): 30-31.
5. Lehmkuhle M J, Vetter R J, Parikh H, et al. Implantable neural interfaces for characterizing population responses to odorants and electrical stimuli in the nurse shark, Ginglymostoma cirratum. Chem Senses, 2006, 31: A14.
6. Hirotaka S. Remote radio control of insect flight. Front Integr Neurosci, 2009, 3: 24.
7. Nobutaka K, Letters M. Artificial control of swimming in goldfish by brain stimulation: confirmation of the midbrain nuclei as the swimming center. Neurosci Lett, 2009, 452(1): 42-46.
8. Seo J, Choi J, Park S. Wireless navigation of pigeons using polyme r-based fully implantable stimulator: a pilot study using depth electrodes// 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Jeju: IEEE, 2017: 917-920.
9. 卞文超, 苏学成. 放飞世界首只机器人鸟. 大众日报, 2007-03-02.
10. 王勇, 苏学成, 槐瑞托, 等. 动物机器人遥控导航系统. 机器人, 2006, 28(2): 183-186.
11. 王勇, 槐瑞托, 王敏, 等. 基于脑微刺激的智能动物的研究. 中国生物医学工程学报, 2006, 25(4): 497-502..
12. 张韶岷, 王鹏, 江君, 等. 大鼠遥控导航及其行为训练系统的研究. 中国生物医学工程学报, 2007, 26(6): 830-836.
13. 谢合瑞, 郭策, 戴振东. 恒流多通道动物机器人遥控刺激系统的研制. 现代电子技术, 2009, 32(4): 68-71.
14. 陈臣. 应用于昆虫的无线微型刺激系统关键技术的研究. 杭州: 杭州电子科技大学, 2017.
15. 彭勇, 王婷婷, 闫艳红, 等. 鲤鱼机器人无线遥控系统设计与应用. 中国生物医学工程学报, 2019, 38(4): 431-437.
16. Zhou Z, Liu D, Sun H. Pigeon robot for navigation guided by remote control: System construction and functional verification. J Bionic Eng, 2021, 18(1): 184-196.
17. 李演明, 陈忠会, 杨晓冰, 等. 一种用于低速电动汽车的锂电池管理系统研究. 电力电子技术, 2018, 52(12): 61-64.
18. Yang P, Yu H Y, Yan Y G. Implementation of the li-ion battery management system based on DS2438. Appl Mech Mater, 2015, 733: 714-717.
19. 曲成树. 安防机器人磷酸铁锂电池管理系统研制. 成都: 电子科技大学, 2019.
20. Zheng L, Zhu J, Wang G. Novel methods for estimating lithium-ion battery state of energy and maximum available energy. Appl Energ, 2016, 178: 1-8.
21. He C. Power tracking and state-of-energy balancing of an energy storage system by distributed control. IEEE Access, 2020, 8: 170261-170270.
22. 苏学成, 槐瑞托, 杨俊卿, 等. 控制动物机器人运动行为的脑机制和控制方法. 中国科学: 信息科学, 2012, 42(9): 1130-1146.
23. 王文波, 戴振东. 动物机器人的研究现状与发展. 机械制造与自动化, 2010, 39(2): 1-7.

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