Light driven robots - flare launching autonomous swimming hydrobot (FLASH)

  • Anthony Le

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)


Light is a readily available, versatile and compact energy source which could power and remotely control a new generation of light-driven robots. Untethered microrobots are not only capable of navigating through varied natural environments but are also able to perform complex tasks within the human body and inside enclosed systems. Light-driven robots can operate safely in convoluted and delicate physiological environments with significant impact on bioengineering and healthcare. The properties of light (intensity, wavelength, and polarisation) could be tailored towards specific requirements.

This thesis will first discuss recent developments in three main photo-actuation methodologies in micro-robotics namely photocatalysis, photovoltaics and photomechanical/photothermal effects. Then, a road map towards autonomous, smart light-driven robots of the future is introduced. After that, a flare launching autonomous swimming hydro-bot (FLASH) is developed as an early realisation of this new class of intelligent light driven robots. Finally, possible future works aiming at developing micro light-driven swimming/ jump gliding robots are discussed. This includes an early investigation into stimuli-responsive, biodegradable soft hydrogels which could offer a new and novel approach to improve FLASH’s performance in areas such as soft body combustion, biocompatibility enhancement (biodegradable materials) and encoded intelligence (stimuli-responsive materials).

This thesis presents a comprehensive investigation into existing and emerging technologies for photo-actuation in microrobots, exploring approaches suitable for in vivo, in vitro and environmental remediations. It demonstrates that it is beneficial to combine different photo-actuation techniques with novel locomotion mechanisms to create self-sufficient, environmentally friendly light driven microrobots which are capable of performing complex tasks.
Date of Award2 Dec 2021
Original languageEnglish
Awarding Institution
  • The University of Bristol
SupervisorJonathan M Rossiter (Supervisor) & Hemma Philamore (Supervisor)

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