Boundaries Control Collective Dynamics of Inertial Self-Propelled Robots

Programming active cohesive granular matter with mechanically induced phase changes

At the macroscale, controlling robotic swarms typically uses substantial memory, processing power, and coordination unavailable at the microscale, e.g., for colloidal robots, which could be useful for fighting disease, fabricating intelligent textiles, and designing nanocomputers. To develop principles that can leverage physical interactions and thus be used across scales, we take a two-pronged approach: a theoretical abstraction of self-organizing particle systems and an experimental robot system of active cohesive granular matter that intentionally lacks digital electronic computation and communication, using minimal (or no) sensing and control. As predicted by theory, as interparticle attraction increases, the collective transitions from dispersed to a compact phase. When aggregated, the collective can transport non-robot "impurities," thus performing an emergent task driven by the physics underlying the transition. These results reveal a fruitful interplay between algorithm design and active matter robophysics that can result in principles for programming collectives without the need for complex algorithms or capabilities.

Emergent Field-Driven Robot Swarm States

We present an ecology-inspired form of active matter consisting of a robot swarm. Each robot moves over a planar dynamic resource environment represented by a large light-emitting diode array in search of maximum light intensity; the robots deplete (dim) locally by their presence the local light intensity and seek maximum light intensity. Their movement is directed along the steepest local light intensity gradient; we call this emergent symmetry breaking motion "field drive." We show there emerge dynamic and spatial transitions similar to gas, crystalline, liquid, glass, and jammed states as a function of robot density, resource consumption rates, and resource recovery rates. Paradoxically the nongas states emerge from smooth, flat resource landscapes, not rough ones, and each state can directly move to a glassy state if the resource recovery rate is slow enough, at any robot density.

Memory effects, arches and polar defect ordering at the cross-over from wet to dry active nematics

We use analytic arguments and numerical solutions of the continuum, active nematohydrodynamic equations to study how friction alters the behaviour of active nematics. Concentrating on the case where there is nematic ordering in the passive limit, we show that, as the friction is increased, memory effects become more prominent and +1/2 topological defects leave increasingly persistent trails in the director field as they pass. The trails are preferential sites for defect formation and they tend to impose polar order on any new +1/2 defects. In the absence of noise and for high friction, it becomes very difficult to create defects, but trails formed by any defects present at the beginning of the simulations persist and organise into parallel arch-like patterns in the director field. We show aligned arches of equal width are approximate steady state solutions of the equations of motion which co-exist with the nematic state. We compare our results to other models in the literature, in particular dry systems with no hydrodynamics, where trails, arches and polar defect ordering have also been observed.

Effects of active crowder size and activity-crowding coupling on polymer translocation

Polymer translocation in complex environments is crucially important to many biological processes in life. In the present work, we adopted two-dimensional Langevin dynamics simulations to study the forced and unbiased polymer translocation dynamics in active and crowded media. The translocation time and probability are analyzed in terms of active force F_a, volume fraction φ and also the crowder size. The non-trivial active crowder size effect and activity-crowding coupling effect as well as the novel mechanism of unbiased translocation between two active environments with different active particle sizes are clarified. Firstly, for forced translocation, we reveal an intriguing non-monotonic dependence of the translocation time on the crowder size in the case of large activity. In particular, crowders of intermediate size similar to the polymer segment are proven to be the most favorable for translocation. Moreover, a facilitation-inhibition crossover of the translocation time with increasing volume fraction is observed, indicating a crucial activity-crowding coupling effect. Secondly, for unbiased translocation driven by different active crowder sizes, the translocation probability demonstrates a novel turnover phenomenon, implying the appearance of an opposite directional preference as the active force exceeds a critical value. The translocation time in both directions decreases monotonically with the active force. The asymmetric activity effect together with the entropic driving scenario provides a reasonable picture for the peculiar behavior observed in unbiased translocation.

Sorting and Extraction of Self-Propelled Chiral Particles by Polarized Wall Currents

The dynamics of self-propelled particles with curved trajectories is investigated. Two modes are observed, a bulk mode with a quasicircular motion and a surface mode with the particles following the walls. The surface mode is the only mode of ballistic transport and the particle current is polar and depends on the particles' chirality. We show that a robust sorting and extraction occurs when the particles explore a domain with two exit gates collecting selectively the particles circling left and right. With a counterslope, the extraction rate is found to increase while the sorting error is reduced.

Boids in a loop: Self-propelled particles within a flexible boundary

We numerically explore the behavior of repelling and aligning self-propelled polar particles (boids) in two dimensions enclosed by a damped flexible and elastic loop-shaped boundary. We observe disordered, polar ordered, jammed, and circulating states. The latter produce a rich variety of boundary shapes, including circles, ovals, irregulars, ruffles, or sprockets, depending upon the bending moment of the boundary and the boundary to particle mass ratio. With the exception of the circulating states with nonround boundaries, states resemble those exhibited by attracting self-propelled particles, but here the confining boundary acts in place of a cohesive force. We attribute the formation of ruffles to instability mediated by pressure on the boundary when the speed of waves on the boundary approximately matches the self-propelled particle's swim speed.

Statistical reprogramming of macroscopic self-assembly with dynamic boundaries

Self-assembly is a ubiquitous process that can generate complex and functional structures via local interactions among a large set of simpler components. The ability to program the self-assembly pathway of component sets elucidates fundamental physics and enables alternative competitive fabrication technologies. Reprogrammability offers further opportunities for tuning structural and material properties but requires reversible selection from multistable self-assembling patterns, which remains a challenge. Here, we show statistical reprogramming of two-dimensional (2D), noncompact self-assembled structures by the dynamic confinement of orbitally shaken and magnetically repulsive millimeter-scale particles. Under a constant shaking regime, we control the rate of radius change of an assembly arena via moving hard boundaries and select among a finite set of self-assembled patterns repeatably and reversibly. By temporarily trapping particles in topologically identified stable states, we also demonstrate 2D reprogrammable stiffness and three-dimensional (3D) magnetic clutching of the self-assembled structures. Our reprogrammable system has prospective implications for the design of granular materials in a multitude of physical scales where out-of-equilibrium self-assembly can be realized with different numbers or types of particles. Our dynamic boundary regulation may also enable robust bottom-up control strategies for novel robotic assembly applications by designing more complex spatiotemporal interactions using mobile robots.

Phase Separation by Entanglement of Active Polymerlike Worms

We investigate the aggregation and phase separation of thin, living T. tubifex worms that behave as active polymers. Randomly dispersed active worms spontaneously aggregate to form compact, highly entangled blobs, a process similar to polymer phase separation, and for which we observe power-law growth kinetics. We find that the phase separation of active polymerlike worms does not occur through Ostwald ripening, but through active motion and coalescence of the phase domains. Interestingly, the growth mechanism differs from conventional growth by droplet coalescence: the diffusion constant characterizing the random motion of a worm blob is independent of its size, a phenomenon that can be explained from the fact that the active random motion arises from the worms at the surface of the blob. This leads to a fundamentally different phase-separation mechanism that may be unique to active polymers.

Properties of balanced flows with bottlenecks: Common stylized facts in finance and vibration-driven vehicles

We study experimentally the properties of the flow of mechanical vibration-driven vehicles confined in two chambers connected through a narrow opening. We report that the density of particles around the opening presents critical behavior and scaling properties. By mapping this density to the financial market price, we document that the main stylized facts observed in financial systems have their counterparts in the mechanical system. The experimental model accurately reproduces financial properties such as scaling of the price fluctuation, volatility clustering, and multiscaling.

The inhibition of concentrated active baths

Passive tracers in the active bath express fascinating behaviors. However, most studies are restricted to dilute active baths. Here, we use 2D simulation of suspensions consisting of active Brownian particles and a passive disk-shaped tracer to investigate tracers' diffusive behaviors in a wide range of volume fractions. Due to the competition between the thermal noise and collisions with active particles, tracers express a first transition from the normal diffusion to the superdiffusion at a short time scale and recur to normal diffusion at a long time scale. At a low volume fraction, infrequent active collisions retard the first transition of smaller tracers. At a high volume fraction, active particles with high activity aggregating around tracers induce a bimodal probability distribution function of tracer displacements during superdiffusion. Considering the enhancement of diffusion, the non-dimensional enhanced diffusivity increases asymptotically with the Peclet number. The asymptotic line gives an upper limit of non-dimensional enhanced diffusivity of tracers. Cases with lower enhanced diffusion have a high volume fraction and a low active velocity that indicates the inhibition of concentrated active baths. With the high negentropic work of these cases, the inhibition is explained as the change of the configuration of active baths for introducing tracers.

Different-shaped micro-objects driven by active particle aggregations

The dynamics of passive micro-objects in an active bath has been receiving much attention. However, the influence of the shapes of micro-objects remains unclear. Here, we use 2D simulation to investigate the interaction between active Brownian particles and different-shaped passive micro-objects. We show that active particles accumulate around micro-objects and self-assemble into living aggregations at a high active velocity and high volume fraction. The shapes of micro-objects affect the distributions of the aggregations. In turn, the different distribution of aggregations influences the motion of micro-objects and induces abnormal diffusive behaviors. We further demonstrate that polar distributed aggregations at a high active velocity and the inhibition of the active bath at a low active velocity induce the counterintuitive anisotropic enhanced diffusion of rods, and the steric interaction between active particles induces the reverse translation-rotation coupled diffusion of chevrons.

Constraint Dependence of Active Depletion Forces on Passive Particles

Using simulations and experiments, we demonstrate that the effective interaction between passive particles in an active bath substantially depends on an external constraint suffered by the passive particles. Particularly, the effective interaction between two free passive particles, which is directly measured in simulation, is qualitatively different from the one between two fixed particles. Moreover, we find that the friction experienced by the passive particles-a kinematic constraint-similarly influences the effective interaction. These remarkable features are in significant contrast to the equilibrium cases, and mainly arise from the accumulation of the active particles near the concave gap formed by the passive spheres. This constraint dependence not only deepens our understanding of the "active depletion force," but also provides an additional tool to tune the effective interactions in an active bath.

Reticulate collisional structure in boundary-driven granular gases

We report a peculiar head-on collision network between two vibrating boundaries in experiments performed during a parabolic flight and in a laboratory using horizontal vibration. This structure is a new ordering, which is due to an orientation correlation between the relative position and velocity of any particle pair. It weakens the collision frequency and produces a long-range boundary effect. Moreover, we find the molecular chaos assumption is violated in a larger portion of the phase space. Using an anisotropic distribution model, we modify angular integration results and compare them to the results of the kinetic theory.

Defect dynamics in clusters of self-propelled rods in circular confinement

Rod-shaped active micro/nano-particles, such as bacterial and bipolar metallic micro/nano-motors, demonstrate novel collective phenomena far from the equilibrium state compared to passive particles. We apply a simulation approach --dissipative particle dynamics (DPD)-- to explore the collectively ordered states of self-propelled rods (SPRs). The SPRs are confined in a finite circular zone and repel each other when two rods touch each other. It is found that for a long enough rods system, the global vortex patterns, dynamic pattern oscillation between hedgehog pattern and vortex pattern, and hedgehog patterns are observed successively with increasing active force F_a. For the vortex pattern, the total interaction energy between the rods U is linear with active force F_a, i.e., U ∼ F_a . While the relation U ∼ F_a² is obtained for the hedgehog structure. It is observed that a new hedgehog pattern with one defect core is created by two ejections of polar cluster in opposite directions from the original hedgehog pattern, and then merges into one through the diffusion of the two aggregates, i.e., the creation and annihilation of topological charges.

Magnetotactic bacteria in a droplet self-assemble into a rotary motor

From intracellular protein trafficking to large-scale motion of animal groups, the physical concepts driving the self-organization of living systems are still largely unraveled. Self-organization of active entities, leading to novel phases and emergent macroscopic properties, recently shed new light on these complex dynamical processes. Here we show that under the application of a constant magnetic field, motile magnetotactic bacteria confined in water-in-oil droplets self-assemble into a rotary motor exerting a torque on the external oil phase. A collective motion in the form of a large-scale vortex, reversable by inverting the field direction, builds up in the droplet with a vorticity perpendicular to the magnetic field. We study this collective organization at different concentrations, magnetic fields and droplet radii and reveal the formation of two torque-generating areas close to the droplet interface. We characterize quantitatively the mechanical energy extractable from this new biological and self-assembled motor.

On-demand orbital maneuver of multiple soft robots via hierarchical magnetomotility

Magnetic soft robots facilitate the battery-free remote control of soft robots. However, parallel control of multiple magnetic robots is challenging due to interference between robots and difficult maneuvers. Here we present the orbital maneuvering of manifold magnetic soft robots. Magneto-induced motion (magnetomotility) that includes the hierarchy of rotation and resultant revolution allows for the independent control of the robot's velocity and orbital radius. The soft robot achieves a speed of 60 body length (BL) s-1, which is approximately 50, 000 times faster with 1/7 the weight of the current lightest legged soft robot. The hierarchical magnetomotility is suitable for versatile locomotion such as stairs and uphill climbing, underwater and above water swimming. Owing to their swimming functionality, a swarm of such soft robots is capable of transportation of cargo. On-demand orbital maneuvering of magnetic soft robots provides a new methodology for concurrent actuation of multiple robots exhibiting collective behaviors.

A robot made of robots: Emergent transport and control of a smarticle ensemble

Robot locomotion is typically generated by coordinated integration of single-purpose components, like actuators, sensors, body segments, and limbs. We posit that certain future robots could self-propel using systems in which a delineation of components and their interactions is not so clear, becoming robust and flexible entities composed of functional components that are redundant and generic and can interact stochastically. Control of such a collective becomes a challenge because synthesis techniques typically assume known input-output relationships. To discover principles by which such future robots can be built and controlled, we study a model robophysical system: planar ensembles of periodically deforming smart, active particles—smarticles. When enclosed, these individually immotile robots could collectively diffuse via stochastic mechanical interactions. We show experimentally and theoretically that directed drift of such a supersmarticle could be achieved via inactivation of individual smarticles and used this phenomenon to generate endogenous phototaxis. By numerically modeling the relationship between smarticle activity and transport, we elucidated the role of smarticle deactivation on supersmarticle dynamics from little data—a single experimental trial. From this mapping, we demonstrate that the supersmarticle could be exogenously steered anywhere in the plane, expanding supersmarticle capabilities while simultaneously enabling decentralized closed-loop control. We suggest that the smarticle model system may aid discovery of principles by which a class of future “stochastic” robots can rely on collective internal mechanical interactions to perform tasks.

Clustering algorithm for formations in football games

In competitive team sports, players maintain a certain formation during a game to achieve effective attacks and defenses. For the quantitative game analysis and assessment of team styles, we need a general framework that can characterize such formation structures dynamically. This paper develops a clustering algorithm for formations of multiple football (soccer) games based on the Delaunay method, which defines the formation of a team as an adjacency matrix of Delaunay triangulation. We first show that heat maps of entire football games can be clustered into several average formations: “442”, “4141”, “433”, “541”, and “343”. Then, using hierarchical clustering, each average formation is further divided into more specific patterns (clusters) in which the configurations of players are different. Our method enables the visualization, quantitative comparison, and time-series analysis for formations in different time scales by focusing on transitions between clusters at each hierarchy. In particular, we can extract team styles from multiple games regarding the positional exchange of players within the formations. Applying our algorithm to the datasets comprising football games, we extract typical transition patterns of the formation for a particular team.

Lifetime distributions for adjacency relationships in a Vicsek model

We investigate the statistical properties of adjacency relationships in a two-dimensional Vicsek model. We define adjacent edges for all particles at every time step by (a) Delaunay triangulation and (b) Euclidean distance, and obtain cumulative distributions P(τ) of lifetime τ of the edges. We find that the shape of P(τ) changes from an exponential to a power law depending on the interaction radius, which is a parameter of the Vicsek model. We discuss the emergence of the power-law distribution from the viewpoint of first passage time problem for a fractional Brownian motion.

Active particles in noninertial frames: How to self-propel on a carousel

Typically the motion of self-propelled active particles is described in a quiescent environment establishing an inertial frame of reference. Here we assume that friction, self-propulsion, and fluctuations occur relative to a noninertial frame and thereby the active Brownian motion model is generalized to noninertial frames. First, analytical solutions are presented for the overdamped case, both for linear swimmers and for circle swimmers. For a frame rotating with constant angular velocity ("carousel"), the resulting noise-free trajectories in the static laboratory frame are trochoids if these are circles in the rotating frame. For systems governed by inertia, such as vibrated granulates or active complex plasmas, centrifugal and Coriolis forces become relevant. For both linear and circling self-propulsion, these forces lead to out-spiraling trajectories which for long times approach a spira mirabilis. This implies that a self-propelled particle will typically leave a rotating carousel. A navigation strategy is proposed to avoid this expulsion, by adjusting the self-propulsion direction at will. For a particle, initially quiescent in the rotating frame, it is shown that this strategy only works if the initial distance to the rotation center is smaller than a critical radius R_{c} which scales with the self-propulsion velocity. Possible experiments to verify the theoretical predictions are discussed.

Characterization and control of a bottleneck-induced traffic-jam transition for self-propelled particles in a track

A collection of self-propelled elongated particles is circulating in a circular track. Due to the presence of a bottleneck, the flow transits to a congested state for a sufficient number of particles, even if the whole track is not saturated. Both experiments and simulations are used to identify the transition toward congestion. An intermediate regime of coexistence is characterized by intermittency between a free flow state and a jammed state. The range of the coexistence region is found to depend explicitly on fluctuating quantities such as the distribution of the escape times from a jam and the headway time distribution between free particles. Optimization strategies, such as the "slower is faster" effect, are tested in experiments and simulations, and an increase in the traffic performances is reported.

Collective oscillation in dense suspension of self-propelled chiral rods

Active particles capable of self-propulsion commonly exhibit rich collective dynamics and have attracted increasing attention due to their applications in biology, robotics, social transport, and biomedicine. However, it remains unclear how the geometric features of active particles affect their collective behaviors. In this paper, we explore the collective dynamics of L-shaped active rods. We show that a dense suspension of self-propelled L-shaped rods exhibits fascinating non-equilibrium oscillatory dynamic clustering. A new oscillation phase can form due to distinct collisions and aggregation mechanisms arising from the L-shaped chirality of elements. A generic diagram of emerging states is provided over a wide range of geometric parameters. Our findings show that the comparative strength between the periodic separation and proximity effect from chirality and the alignment effect from elongated geometry drive the formation and transition of dynamic patterns. This chirality-triggered oscillation phase suggests a new route to understand active matter and paves a way for emerging applications.

Dynamics of a Self-Propelled Particle in a Harmonic Trap

The dynamics of an active walker in a harmonic potential is studied experimentally, numerically, and theoretically. At odds with usual models of self-propelled particles, we identify two dynamical states for which the particle condensates at a finite distance from the trap center. In the first state, also found in other systems, the particle points radially outward from the trap, while diffusing along the azimuthal direction. In the second state, the particle performs circular orbits around the center of the trap. We show that self-alignment, taking the form of a torque coupling the particle orientation and velocity, is responsible for the emergence of this second dynamical state. The transition between the two states is controlled by the persistence of the particle orientation. At low inertia, the transition is continuous. For large inertia, the transition is discontinuous and a coexistence regime with intermittent dynamics develops. The two states survive in the overdamped limit or when the particle is confined by a curved hard wall.

Inertial delay of self-propelled particles

The motion of self-propelled massive particles through a gaseous medium is dominated by inertial effects. Examples include vibrated granulates, activated complex plasmas and flying insects. However, inertia is usually neglected in standard models. Here, we experimentally demonstrate the significance of inertia on macroscopic self-propelled particles. We observe a distinct inertial delay between orientation and velocity of particles, originating from the finite relaxation times in the system. This effect is fully explained by an underdamped generalisation of the Langevin model of active Brownian motion. In stark contrast to passive systems, the inertial delay profoundly influences the long-time dynamics and enables new fundamental strategies for controlling self-propulsion in active matter.