Gen-next robots powered by light-sensitive muscle developed in US

The research team

Washington: Researchers have developed a new generation of two-tailed robots that are driven by light-activated muscle tissue – an advance that brings engineers a step closer to building autonomous biobots.

Researchers led by Taher Saif of the University of Illinois in the US, designed a new generation of two-tailed bots powered by skeletal muscle tissue that was stimulated by on-board motor neurons. The neurons upon exposure to light, fired to move the muscles, the study, published in the journal PNAS, noted.

“We applied an optogenetic neuron cell culture, derived from mouse stem cells, adjacent to the muscle tissue,” Saif said. The neurons, he added, advanced toward the muscle and formed neuromuscular junctions, and the swimmer assembled on its own. After ensuring that the neuromuscular tissue worked well with their synthetic biobot skeletons, the team optimised the bot’s functions.

“We used computational models, led by mechanical science and engineering professor Mattia Gazzola, to determine which physical attributes would lead to the fastest and most efficient swimming,” Saif said. He added that the researchers looked at variations in the number of tails and tail lengths for finding the most efficient design of the bot.

“Given the fact that biological actuators, or biobots, are not as mature as other technologies, they are unable to produce large forces. This makes their movement hard to control,” Gazzola, also from University of Illinois, said. He added that it was very important to carefully design the scaffold the biobots grew around and interacted with to make the most out of the technology and achieve locomotive functions.

“The computer simulations we run play a critical role in this task as we can span a number of possible designs and select only the most promising ones for testing in real life,” Gazzola said. Saif added that the ability to drive muscle activity with neurons is an advance that paves the way for further integration of neural units within biohybrid systems.

“Given our understanding of neural control in animals, it may be possible to move forward with biohybrid neuromuscular design by using a hierarchical organization of neural networks,” Saif added.