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Research Article | Online first | Published: 13 March 2024

Highly adaptive triboelectric tactile sensor on the foot of autonomous wall-climbing robots for detecting the adhesion state and avoiding the hazard

Show Author's Information Zhaoyang Wang1,§,  Jianhua Liu1,§,  Ziyu Wang1,§,  Chang Liu1,  Qingyu Chen2,  Chaofan Zhang2,  Wenbo Zhang3,  Jicang Si1,  Xiu Xiao1( ),  Peng Xu1,4( ),  Minyi Xu1( )
Dalian Key Lab of Marine Micro/Nano Energy and Self-powered System, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
Information Science and Technology College, Dalian Maritime University, Dalian 116026, China
Navigation College, Dalian Maritime University, Dalian 116026, China
Intelligent Biomimetic Design Lab, College of Engineering, Peking University, Beijing 100871, China

§ Zhaoyang Wang, Jianhua Liu, and Ziyu Wang contributed equally to this work.

Keywords:
tactile perception, triboelectric sensor, legged wall-climbing robot, ship inspection
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Sensors
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Wang Z, Liu J, Wang Z, et al. Highly adaptive triboelectric tactile sensor on the foot of autonomous wall-climbing robots for detecting the adhesion state and avoiding the hazard. Nano Research, 2024, https://doi.org/10.1007/s12274-024-6537-1
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Abstract Full text Electronic supplementary material About this article

Due to the excellent maneuverability and obstacle crossing of legged robots, it is possible for an autonomous legged wall-climbing robots to replace manual inspection of ship exterior panels. However, when the magnetic adsorption legged wall-climbing robot steps on the convex point or convex line of the wall, or even when the robot missteps, the robot is likely to detach from the ferromagnetic wall. Therefore, this paper proposes a tactile sensor for the legged magnetic adsorption wall-climbing robot to detect the magnetic adsorption state and improve the safety of the autonomous crawling of the robot. The tactile sensor mainly comprises a three-dimensional (3D)-printed shell, a tactile slider, and three isometric sensing units, with an optimized geometry. The experiment shows that the triboelectric tactile sensor can monitor the sliding depth of the tactile slider and control the light-emitting device (LED) signal light. In addition, in the demonstration experiment of detecting the adsorption state of the robot's foot, the triboelectric tactile sensor has strong adaptability to various ferromagnetic wall surfaces. Finally, this study establishes a robot gait control system to verify the feedback control ability of the triboelectric tactile sensor. The results show that the robot equipped with the triboelectric tactile sensor can recognize the dangerous area on the crawling wall and autonomously avoid the risk. Therefore, the proposed triboelectric tactile sensor has great potential in realizing the tactile sensing ability of robots and enhancing the safety and intelligent inspection of ultra-large vessels.


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About this article

Highly adaptive triboelectric tactile sensor on the foot of autonomous wall-climbing robots for detecting the adhesion state and avoiding the hazard

Show Author's information Zhaoyang Wang1,§, Jianhua Liu1,§, Ziyu Wang1,§, Chang Liu1, Qingyu Chen2, Chaofan Zhang2, Wenbo Zhang3, Jicang Si1, Xiu Xiao1( ), Peng Xu1,4( ), Minyi Xu1( )
Dalian Key Lab of Marine Micro/Nano Energy and Self-powered System, Marine Engineering College, Dalian Maritime University, Dalian 116026, China
Information Science and Technology College, Dalian Maritime University, Dalian 116026, China
Navigation College, Dalian Maritime University, Dalian 116026, China
Intelligent Biomimetic Design Lab, College of Engineering, Peking University, Beijing 100871, China

§ Zhaoyang Wang, Jianhua Liu, and Ziyu Wang contributed equally to this work.

Abstract

Due to the excellent maneuverability and obstacle crossing of legged robots, it is possible for an autonomous legged wall-climbing robots to replace manual inspection of ship exterior panels. However, when the magnetic adsorption legged wall-climbing robot steps on the convex point or convex line of the wall, or even when the robot missteps, the robot is likely to detach from the ferromagnetic wall. Therefore, this paper proposes a tactile sensor for the legged magnetic adsorption wall-climbing robot to detect the magnetic adsorption state and improve the safety of the autonomous crawling of the robot. The tactile sensor mainly comprises a three-dimensional (3D)-printed shell, a tactile slider, and three isometric sensing units, with an optimized geometry. The experiment shows that the triboelectric tactile sensor can monitor the sliding depth of the tactile slider and control the light-emitting device (LED) signal light. In addition, in the demonstration experiment of detecting the adsorption state of the robot's foot, the triboelectric tactile sensor has strong adaptability to various ferromagnetic wall surfaces. Finally, this study establishes a robot gait control system to verify the feedback control ability of the triboelectric tactile sensor. The results show that the robot equipped with the triboelectric tactile sensor can recognize the dangerous area on the crawling wall and autonomously avoid the risk. Therefore, the proposed triboelectric tactile sensor has great potential in realizing the tactile sensing ability of robots and enhancing the safety and intelligent inspection of ultra-large vessels.

Keywords: tactile perception, triboelectric sensor, legged wall-climbing robot, ship inspection

References(45)

[1]
Vlasova, N. S.; Bykov, N. V. The problem of adhesion methods and locomotion mechanism development for wall-climbing robots. 2019, arXiv: 1905.09214. arXiv.org e-Print archive. https://arxiv.org/abs/1905.09214 (accessed May 22, 2019).
[2]
Hajeer, A.; Chen, L.; Hu, E. Review of classification for wall climbing robots for industrial inspection applications. In Proceedings of the 2020 IEEE 16th International Conference on Automation Science and Engineering, Hong Kong, China, 2020, pp 1421–1426.
DOI
[3]

Fang, Y.; Wang, S.; Bi, Q. S.; Cui, D.; Yan, C. L. Design and technical development of wall-climbing robots: A review. J. Bionic Eng. 2022, 19, 877–901.
DOI Google Scholar
[4]

Huang, H. C.; Li, D. H.; Xue, Z.; Chen, X. L.; Liu, S. Y.; Leng, J. X.; Wei, Y. Design and performance analysis of a tracked wall-climbing robot for ship inspection in shipbuilding. Ocean Eng. 2017, 131, 224–230.
DOI Google Scholar
[5]

Wang, B.; Ni, Z. F.; Shen, Y.; Zhang, S.; Shen, Q.; Niu, X. W. Design and analysis of a wheel-leg compound variable curvature ship hull cleaning robot. Ocean Eng. 2022, 266, 112755.
DOI Google Scholar
[6]
Silva, M. F.; Machado, J. A. T.; Tar, J. K. A survey of technologies for climbing robots adhesion to surfaces. In Proceedings of 2008 IEEE International Conference on Computational Cybernetics, Stara Lesna, Slovakia, 2008, pp 127–132.
DOI
[7]
Kapula, P. R.; Ram, M. B.; Chakradhar, M. S.; Shravani, K.; Akhilesh, K.; Likhitha, K. L. Design of an adhesion-based wall climbing robot. In Proceedings of the 2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Vellore, India, 2023, pp 1–6.
DOI
[8]

Hu, J. Y.; Han, X.; Tao, Y. R.; Feng, S. Z. A magnetic crawler wall-climbing robot with capacity of high payload on the convex surface. Robot. Auton. Syst. 2022, 148, 103907.
DOI Google Scholar
[9]

Zhu, L. S.; Zheng, X. S. Design of a curved surface adaptive permanent magnet wall climbing robot. J. Phys. Conf. Ser. 2022, 2405, 012028.
DOI Google Scholar
[10]

Hong, S.; Um, Y.; Park, J.; Park, H. W. Agile and versatile climbing on ferromagnetic surfaces with a quadrupedal robot. Sci. Robot. 2022, 7, eadd1017.
DOI Google Scholar
[11]

Zhu, H. F.; Guan, Y. S.; Wu, W. Q.; Zhang, L. M.; Zhou, X. F.; Zhang, H. Autonomous pose detection and alignment of suction modules of a biped wall-climbing robot. IEEE/ASME Trans. Mechatron. 2015, 20, 653–662.
DOI Google Scholar
[12]

Kim, T.; Hong, I.; Kim, M.; Im, S.; Roh, Y.; Kim, C.; Lim, J.; Kim, D.; Park, J.; Lee, S. et al. Ultra-stable and tough bioinspired crack-based tactile sensor for small legged robots. npj Flex. Electron. 2023, 7, 22.
DOI Google Scholar
[13]
Zainal Abidin, M. S.; Amin, S. H. M. On the development a pneumatic four-legged mechanism autonomous vertical wall climbing robot. In Proceedings of 1998 Malaysian Science and Techology Congress, Pulan Pinang, Malaysia, 1999.
[14]

Li, R.; Yan, S.; Zhou, C. C.; Liu, Z. B.; Shou, M. J. Design of the paw of wall-climbing robot with spiny and sensing function. J. Phys. Conf. Ser. 2023, 2537, 12009.
DOI Google Scholar
[15]

Aslam, D. M.; Dangi, G. D. Design, fabrication and testing of a smart robotic foot. Robot. Auton. Syst. 2005, 51, 207–214.
DOI Google Scholar
[16]

Zhang, H. X.; Zhang, J. W.; Zong, G. H.; Wang, W.; Liu, R. Sky cleaner 3: A real pneumatic climbing robot for glass-wall cleaning. IEEE Robot. Autom. Mag. 2006, 13, 32–41.
DOI Google Scholar
[17]

Hu, B. S.; Xue, J. T.; Jiang, D. J.; Tan, P. C.; Wang, Y. Q.; Liu, M. H.; Yu, H. L.; Zou, Y.; Li, Z. Wearable exoskeleton system for energy harvesting and angle sensing based on a piezoelectric cantilever generator array. ACS Appl. Mater. Interfaces 2022, 14, 36622–36632.
DOI Google Scholar
[18]

Zou, Y.; Gai, Y. S.; Tan, P. C.; Jiang, D. J.; Qu, X. C.; Xue, J. T.; Ouyang, H.; Shi, B. J.; Li, L. L.; Luo, D. et al. Stretchable graded multichannel self-powered respiratory sensor inspired by shark gill. Fundam. Res. 2022, 18, 619–628.
DOI Google Scholar
[19]

Liu, J. H.; Xu, P.; Zheng, J. X.; Liu, X. Y.; Wang, X. Y.; Wang, S. Y.; Guan, T. Z.; Xie, G. M.; Xu, M. Y. Whisker-inspired and self-powered triboelectric sensor for underwater obstacle detection and collision avoidance. Nano Energy 2022, 101, 107633.
DOI Google Scholar
[20]

Xu, P.; Liu, J. H.; Liu, X. Y.; Wang, X. Y.; Zheng, J. X.; Wang, S. Y.; Chen, T. Y.; Wang, H.; Wang, C.; Fu, X. P. et al. A bio-inspired and self-powered triboelectric tactile sensor for underwater vehicle perception. npj Flex. Electron. 2022, 6, 25.
DOI Google Scholar
[21]

Xu, P.; Wang, X. Y.; Wang, S. Y.; Chen, T. Y.; Liu, J. H.; Zheng, J. X.; Li, W. X.; Xu, M. Y.; Tao, J.; Xie, G. M. A triboelectric-based artificial whisker for reactive obstacle avoidance and local mapping. Research 2021, 2021, 9864967.
DOI Google Scholar
[22]

Song, Z. W.; Yin, J. H.; Wang, Z. H.; Lu, C. Y.; Yang, Z.; Zhao, Z. H.; Lin, Z. N.; Wang, J. Y.; Wu, C. S.; Cheng, J. et al. A flexible triboelectric tactile sensor for simultaneous material and texture recognition. Nano Energy 2022, 93, 106798
DOI Google Scholar
[23]

Jose, J.; Dinakaran, D.; Ramya, M. M.; Harris Samuel, D. G. A survey on magnetic wall-climbing robots for inspection. Int. J. Mech. Prod. Eng. Res. Dev. 2018, 8, 59–68.
DOI Google Scholar
[24]
Wang, S. Y. Research status and future development of wall-climbing robot. In Proceedings of 2021 International Conference on Electronics, Circuits and Information Engineering, Zhengzhou, China, 2021, pp 122–130.
[25]

Chen, X. L.; Wu, Y. P.; Hao, H. D.; Shi, H. L.; Huang, H. C. Tracked wall-climbing robot for calibration of large vertical metal tanks. Appl. Sci. 2019, 9, 2671.
DOI Google Scholar
[26]

Xu, Z. L.; Ma, P. S. A wall-climbing robot for labelling scale of oil tank’s volume. Robotica 2002, 20, 209–212.
DOI Google Scholar
[27]

Meng, H. Y.; Yu, Q.; Liu, Z.; Gai, Y. S.; Xue, J. T.; Bai, Y.; Qu, X. C.; Tan, P. C.; Luo, D.; Huang, W. W. et al. Triboelectric performances of biodegradable polymers. Matter 2023, 6, 4274–4290.
DOI Google Scholar
[28]

Li, Y. H.; Yu, J. R.; Wei, Y. C.; Wang, Y. F.; Feng, Z. Y.; Cheng, L. Q.; Huo, Z. W.; Lei, Y. Q.; Sun, Q. J. Recent progress in self-powered wireless sensors and systems based on TENG. Sensors 2023, 23, 1329.
DOI Google Scholar
[29]

Liu, J. R.; Huang, H.; Zhou, Q.; Wu, C. Self-powered downhole drilling tools vibration sensor based on triboelectric nanogenerator. IEEE Sens. J. 2022, 22, 2250–2258.
DOI Google Scholar
[30]

Zhu, J.; Hou, X. J.; Niu, X. S.; Guo, X. P.; Zhang, J.; He, J.; Guo, T.; Chou, X. J.; Xue, C. Y.; Zhang, W. D. The d-arched piezoelectric-triboelectric hybrid nanogenerator as a self-powered vibration sensor. Sens. Actuators A Phys. 2017, 263, 317–325.
DOI Google Scholar
[31]

Zhao, H. F.; Shu, M. R.; Ai, Z. H.; Lou, Z. R.; Sou, K. W.; Lu, C. Y.; Jin, Y. C.; Wang, Z. H.; Wang, J. Y.; Wu, C. S. et al. A highly sensitive triboelectric vibration sensor for machinery condition monitoring. Adv. Energy Mater. 2022, 12, 2201132.
DOI Google Scholar
[32]

Li, P.; Liu, Y. B.; Zhang, H.; Hu, Z. P.; Jia, L. N.; Liu, D. K.; Yu, L.; Li, B.; Yao, Y. W. All-nanofiber self-powered PTFE/PA66 device for real-time breathing monitor by scalable solution blow spinning technology. Nano Res. 2022, 15, 8458–8464.
DOI Google Scholar
[33]

Xu, J. H.; Wei, X. L.; Li, R. N.; Shi, Y. P.; Peng, Y. T.; Wu, Z. Y.; Wang, Z. L. Intelligent self-powered sensor based on triboelectric nanogenerator for take-off status monitoring in the sport of triple-jumping. Nano Res. 2022, 15, 6483–6489.
DOI Google Scholar
[34]

Das, P. S.; Chhetry, A.; Maharjan, P.; Rasel, M. S.; Park, J. Y. A laser ablated graphene-based flexible self-powered pressure sensor for human gestures and finger pulse monitoring. Nano Res. 2019, 12, 1789–1795.
DOI Google Scholar
[35]

Tan, P. C.; Han, X.; Zou, Y.; Qu, X. C.; Xue, J. T.; Li, T.; Wang, Y. Q.; Luo, R. Z.; Cui, X.; Xi, Y. et al. Self-powered gesture recognition wristband enabled by machine learning for full keyboard and multicommand input. Adv. Mater. 2022, 34, 2200793.
DOI Google Scholar
[36]

Yang, Q. Y.; Yang, S. Q.; Qiu, P. F.; Peng, L. M.; Wei, T. R.; Zhang, Z.; Shi, X.; Chen, L. D. Flexible thermoelectrics based on ductile semiconductors. Science 2022, 377, 854–858.
DOI Google Scholar
[37]
Liu, J. H.; Xu, P.; Liu, B.; Xi, Z. Y.; Li, Y. Z.; Guo, L. N.; Guan, T. Z.; Zhu, P.; Meng, Z. C.; Wang, S. Y. et al. Underwater biomimetic lateral line sensor based on triboelectric nanogenerator for dynamic pressure monitoring and trajectory perception. Small, in press, DOI: 10.1002/smll.202308491.
DOI
[38]

Wang, Y.; Wu, C.; Yang, S. A self-powered rotating speed sensor for downhole motor based on triboelectric nanogenerator. IEEE Sens. J. 2021, 21, 4310–4316.
DOI Google Scholar
[39]

Zhang, X. S.; Gao, Q.; Gao, Q.; Yu, X.; Cheng, T. H.; Wang, Z. L. Triboelectric rotary motion sensor for industrial-grade speed and angle monitoring. Sensors 2021, 21, 1713.
DOI Google Scholar
[40]

Qin, Y. H.; Fu, X. P.; Lin, Y.; Wang, Z.; Cao, J.; Zhang, C. Self-powered internet of things sensing node based on triboelectric nanogenerator for sustainable environmental monitoring. Nano Res. 2023, 16, 11878–11884.
DOI Google Scholar
[41]

Zhang, B. S.; Li, W. B.; Ge, J. W.; Chen, C. G.; Yu, X.; Wang, Z. L.; Cheng, T. H. Single-material-substrated triboelectric-electromagnetic hybrid generator for self-powered multifunctional sensing in intelligent greenhouse. Nano Res. 2023, 16, 3149–3155.
DOI Google Scholar
[42]

Cheng, T. H.; Shao, J. J.; Wang, Z. L. Triboelectric nanogenerators. Nat. Rev. Methods Primers 2023, 3, 39.
DOI Google Scholar
[43]

Zhou, Y. K.; Shen, M. L.; Cui, X.; Shao, Y. C.; Li, L. J.; Zhang, Y. Triboelectric nanogenerator based self-powered sensor for artificial intelligence. Nano Energy 2021, 84, 105887.
DOI Google Scholar
[44]

Kim, W. G.; Kim, D. W.; Tcho, I. W.; Kim, J. K.; Kim, M. S.; Choi, Y. K. Triboelectric nanogenerator: Structure, mechanism, and applications. ACS Nano 2021, 15, 258–287.
DOI Google Scholar
[45]

Gao, Q.; Cheng, T. H.; Wang, Z. L. Triboelectric mechanical sensors—Progress and prospects. Extreme Mech. Lett. 2021, 42, 101100.
DOI Google Scholar
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Publication history
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Acknowledgements

Publication history

Received: 13 December 2023
Revised: 26 January 2024
Accepted: 02 February 2024
Published: 13 March 2024

Copyright

© Tsinghua University Press 2024

Acknowledgements

Acknowledgements

This work was supported by the Dalian Outstanding Young Scientific and Technological Talents Project (No. 2021RJ11), and the Science and Technology Innovation Foundation of Dalian (No. 2021JJ12GX028).

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