Researchers have developed “smart swarms” of miniature robots drawing inspiration from natural ecosystems and observing fish schools, beehives, and ant colonies.
These swarms collaborate through engineered social interactions enabling them to function as a cohesive unit. These interactions allow the collective to overcome obstacles and dangers better as a team than their individual selves.
According to the team, this has resulted in them handling tasks more effectively than they could if they were moving independently or at random.
Significance of time delay
The dynamics of collective motion are influenced by various factors, including density, perturbation, velocity, boundary, and, more notably, time delay.
Time delay— inherent in every system due to finite information transmission among agents— significantly affects collective behaviors. Previous studies show that introducing fixed-time delays can lead to multistability, instabilities, and oscillations. Thereby offering alternative explanations for observed behaviors in nature and aiding advancements in swarm robotics.
Properly incorporating time delays can enhance the persistence of collective structures in noisy environments. Yet, it may reduce their responsiveness to nontrivial external stimuli as agents struggle to distinguish them from noise.
Thus, a tradeoff exists between persistence and responsivity in collective motion due to fixed time delays. According to the research team, this understanding is crucial for designing effective collective systems that balance the need for sustained movement while swiftly responding to environmental cues.
The group programmed an adaptive time delay feature in the robot swarms. The function uses an optical feedback system with controlled light patterns to collectively drive these microrobots.
The feature enables every microrobot in the swarm to modify its mobility in response to environmental changes. By doing this, the swarm showed a significant increase in responsivity without decreasing its robustness— the ability to quickly respond to any environmental change while maintaining the integrity of the swarm.
Navigating complex environments
According to the team, there is potential for scalability and integration into larger machinery with the adaptive time delay technique. This strategy could greatly improve the autonomous drone fleets’ operational efficiency.
In a similar vein, it might make it possible for automobile and truck convoys to travel long distances on the highway together while maintaining better responsiveness and robustness.
These machines will be able to follow and communicate with each other in the same manner as schools of fish. This eliminates the requirement for any form of centralized control, which requires additional data and energy to run.
“Nanorobots, on an individual basis, are vulnerable to complex environments; they struggle to navigate effectively in challenging conditions such as bloodstreams or polluted waters,” said Zhihan Chen, a student at UT at Austin and co-author of the paper, in a statement.
Utilizing collective motion enables them to navigate complex environments more effectively and efficiently, reaching targets while evading obstacles and threats.
Having demonstrated swarm mentality in a laboratory setting, the team introduced further obstacles for evaluation. These tests were carried out in a static liquid solution. The next step is to replicate the action in a moving liquid. They will then proceed to duplicate it within an organism.
Researchers claim that when completely developed, these intelligent swarms could act as sophisticated drug delivery systems. These swarms would find their way through the body and get past its defenses to deliver medication to the intended location.
Alternatively, they could function similarly to iRobot robotic vacuums, but for tainted water, they thoroughly clean a region as a group.
The details of the team’s research were published in the journal Science Advances.
Study Abstract
It is beneficial for collective structures to simultaneously have high persistence to environmental noise and high responsivity to nontrivial external stimuli. However, without the ability to differentiate useful information from noise, there is always a tradeoff between persistence and responsivity within the collective structures. To address this, we propose adaptive time delay inspired by the adaptive behavior observed in the school of fish. This strategy is tested using particles powered by optothermal fields coupled with an optical feedback-control system.
By applying the adaptive time delay with a proper threshold, we experimentally observe the responsivity of the collective structures enhanced by approximately 1.6 times without sacrificing persistence. Furthermore, we integrate adaptive time delay with long-distance transportation and obstacle-avoidance capabilities to prototype adaptive swarm microrobots. This research demonstrates the potential of adaptive time delay to address the persistence-responsivity tradeoff and lays the foundation for intelligent swarm micro/nanorobots operating in complex environments.
