Engineering Sensorial Delay to Control Phototaxis and Emergent Collective Behaviors

Abstract

Collective motions emerging from the interaction of autonomous mobile individuals play a key role in many phenomena, from the growth of bacterial colonies to the coordination of robotic swarms. For these collective behaviors to take hold, the individuals must be able to emit, sense, and react to signals. When dealing with simple organisms and robots, these signals are necessarily very elementary; e.g., a cell might signal its presence by releasing chemicals and a robot by shining light. An additional challenge arises because the motion of the individuals is often noisy; e.g., the orientation of cells can be altered by Brownian motion and that of robots by an uneven terrain. Therefore, the emphasis is on achieving complex and tunable behaviors from simple autonomous agents communicating with each other in robust ways. Here, we show that the delay between sensing and reacting to a signal can determine the individual and collective long-term behavior of autonomous agents whose motion is intrinsically noisy. We experimentally demonstrate that the collective behavior of a group of phototactic robots capable of emitting a radially decaying light field can be tuned from segregation to aggregation and clustering by controlling the delay with which they change their propulsion speed in response to the light intensity they measure. We track this transition to the underlying dynamics of this system, in particular, to the ratio between the robots' sensorial delay time and the characteristic time of the robots' random reorientation. Supported by numerics, we discuss how the same mechanism can be applied to control active agents, e.g., airborne drones, moving in a three-dimensional space. Given the simplicity of this mechanism, the engineering of sensorial delay provides a potentially powerful tool to engineer and dynamically tune the behavior of large ensembles of autonomous mobile agents; furthermore, this mechanism might already be at work within living organisms such as chemotactic cells.

Propagating interfaces in mixtures of active and passive Brownian particles

“…Our results should be relevant and helpful for the interpretation of experiments of mixtures of passive and active colloids [3][4][5][6]18], polar and apolar vibrated disks [37] or even specially programmed robots [38,39]. Thereby, the interface propagation can be identified via w ( ) S q, in scattering experiments or by direct observation.…”

Metastable clusters and channels formed by active particles with aligning interactions

“…Then, in 1995, Vicsek and coauthors introduced the Vicsek model [5], where a swarm is modelled by a collection of active particles moving with constant speed and tending to align with the average direction of motion of the particles in their local neighbourhood; this was first model that considered collective motion in terms of a noise-induced phase transition. Later, several additional models have been introduced to capture the properties of collective behaviours [6][7][8][9][10][11][12].…”

“…Beyond its intrinsic scientific interest, a deep understanding of collective behaviours can contribute to applications in, e.g., swarm robotics, autonomous vehicles and high-accuracy cancer treatment [1,18,19]. In fact, the models employed to describe collective behaviours have also been fruitfully exploited in order to build artificial systems with robust behaviours arising from interactions between very simple constituent agents [9,10,14,20,21]. Furthermore, there is interest in understanding how these behaviours are influenced by the properties of the environment and, in particular, by the presence of obstacles, topological features and other particles [1,17,[22][23][24].…”

Effects of hydrodynamic interactions on rectified transport of self-propelled particles

“…Unlike passive Brownian ratchets, active ratchets do not require the application of an external driving force to produce rectification [2][3][4]. Experimental studies [5][6][7][8][9][10][11][12][13][14][15] have shown the key role of self-propulsion for rectifying particle motion in different structures, such as an array of asymmetric funnels [5], a nanosized ratchet-shaped wheel [6], the asymmetric barriers [8], the microtubule bundles [9], the microscopic gears [11], and the nanoliter chambers [15]. Active ratchet effects and variations on them will open a wealth of possibilities such as sorting, cargo transport, or micromachine construction.…”