Magnetically-triggered ultrafast soft robots with embedded magnetic cognition and feedback control


Magnetically-triggered ultrafast soft robots with embedded magnetic cognition and feedback control

Wang, X.; Canon Bermudez, G. S.; Faßbender, J.; Makarov, D.

In the last years, soft robots have been designed and developed to fulfil demands of better malleability and adaptability to changing environment [1-2]. They can be made of various stimuli responsive materials, which respond to magnetic field [3], light [4], temperature [5], electric fields [6], chemicals [7], pressure [8], etc. In contrast to other actuation mechanisms, magnetic fields are appealing for numerous application scenarios (e.g. environmental, biological, medical), where their long-range penetration, easy accessibility, and controllability [2, 9, 10] offer exciting advantages. Despite the significant advances in soft magnetic actuators, real-time monitoring and precise feedback control [11-13] remain a challenge for magnetic soft robots.

Here, we present a soft robotic system capable of precisely controlling its deformation degree by means of embedded highly compliant, high-performance magnetic sensors. Our ultrathin (7-100 μm) and ultrafast soft robots that can be actuated by in external magnetic fields pulsating at rates of up to 200 Hz. The high-performance magnetic field sensor is based on the giant magnetoresistive effect and is prepared on ultrathin polymeric foils [14-17] to assure its high mechanical stability combined with mechanical imperceptibility. The latter is crucial to avoid any disturbance of the soft actuator due to the presence of magnetic sensing device. The self-sensing function is realized by monitoring the change of the sensor signal upon approaching it to a magnetic patch applied to the soft robot. This concept of an entirely soft and integrated sensor-actuator system enables contactless self-tracking of motion for magnetic soft robots and can be readily extended to other stimuli-driven soft actuators. These developments will pave the way towards intelligent soft robots, autonomous and reactive soft devices, and new types of human-robot interaction.

[1] D. Rus et al., Nature 521, 467 (2015)
[2] L. Hines et al., Adv. Mater. 29, 13 (2017)
[3] J. Y. Kim et al., Nat Mat. 10, 747 (2011)
[4] J. Deng et al., J. Am. Chem. Soc. 138, 225 (2016)
[5] Y. S. Kim et al., Nat Mat. 14, 1002 (2015)
[6] T. Mirfakhrai et al., Materials Today 10, 30 (2007)
[7] Q. Zhao et al., Nat Commun 5 (2014)
[8] SA. Morin et al., Science 337, 828 (2012)
[9] W. Hu et al., Nature 554, 81(2018)
[10] Kim. Y, et al., Nature 558, 274 (2018)
[11] T. G. Thuruthel et al., Sci Robot. 4, eaav1488 (2019)
[12] J. A. Lewis et al., Adv. Mater. 30, 1706383 (2018)
[13] W. Zhang et al., Adv Funct Mater. 29, 1806057 (2019)
[14] M. Melzer et al., Adv. Mater. 27, 1274 (2015)
[15] G. S. C. Bermúdez et al., Nat Electron. 1, 589 (2018)
[16] G. S. C. Bermúdez et al., Sci Adv., 4, eaao2623 (2018)
[17] P. N. Granell et al., npj Flexible Electronics, 3, 3 (2018)

Keywords: Soft robot; magnetic sensor; feedback control

Involved research facilities

Related publications

  • Lecture (Conference)
    Materials Research Society Fall Meeting, 01.-06.12.2019, Boston, USA

Permalink: https://www.hzdr.de/publications/Publ-30389