ABSTRACT. Insect swarms are a model system for understanding collective behavior where the collective motion appears in disorder. To initiate and maintain a swarm in place, flying insects often use a visual external cue called a marker. In mosquitoes, understanding the swarming behavior and its relation to the marker has an additional medical relevance since swarming often precedes mating in the wild, thus constituting an important stage to intercept for controlling mosquito population. In this paper, we conduct experiments to characterize the visual coupling between a swarm of mosquitoes and a marker. A laboratory microcosm with artificial lighting was built to stimulate swarming in the malarial mosquito \emph{Anopheles stephensi}. The microcosm was used to film a mosquito swarm with a stereo camera system as a marker was moved back-and-forth with five different frequencies. System identification analysis of the frequency response shows that the relationship between the swarm and the marker can be described by delayed second order dynamics in a feedback loop. Further, the length of the internal time delay appears to correlate with the number of mosquitoes swarming on the marker indicating that such a delay may be able capture social interactions within swarming systems. For insect swarms, model fitting of trajectory data provides a way to numerically compare swarming behaviors of different species with respect to marker characteristics. These preliminary results motivate linear dynamic systems as a modeling framework for flying insect swarms.

ABSTRACT. This note considers the constrained H-infinity consensus of multi-agent networks with nonidentical constraint sets. An improved distributed algorithm is adopted and a nonlinear controlled output function is defined to evaluate the effect of disturbances. Then, it is shown that the constrained H-infinity consensus can be achieved if some linear matrix inequality has positive solution. Finally, the theoretical results were examined by simulation example.

ABSTRACT. As of February 2021, COVID-19 has spread globally, causing severe economic damage. Although the minimization of human contact is effective in managing outbreaks, it results in severe economic losses. Thus, strategies are required for solving this dilemma by considering the interrelation between the spread of the virus and economic activities. We previously proposed an abstract agent-based model for the COVID-19 outbreak that accounts for economic activities. In this paper, we review the proposed model and present the new simulation results.

ABSTRACT. Swarms and multi-agent systems do not require global communication throughout the swarm for collaboration, nor is it desirable from a bandwidth perspective. Localized communication is necessary in swarms because of the lack of demand for every single agent in a swarm to communicate. Agents can utilize Line-of-sight methods to communicate with each other for localized communication. We propose a system using a digital camera and LEDs to communicate between agents. Each agent would have a digital video camera and LED cluster. Using a camera allows many agents to communicate to a single agents at once using Regions of Interest (ROI). The camera has an added benefit of knowing the spatial location of an agent sending information relative to the agent receiving information. This paper outlines our ideas for swarms to utilize visible light communication (VLC) with a camera and LED cluster.

ABSTRACT. The paper investigates min-consensus control of multi-agent systems with sampled information and limited communication data rate. First, a novel biased quantizer and a non-exponential scaling function are constructed, and accordingly a group of encoders and decoders are proposed. By means of the proposed encoders and decoders, the communication data rate constraints of the multi-agent systems are satisfied. Additionally, based upon the decoded states, the sampling-time min-consensus control input is proposed, so that the states of agents can asymptotically converge to the minimum initial value.

ABSTRACT. This study tackles the task for swarm robotics where robots explore the environment to detect many targets. When a robot detects a target, the robot must be connected with a base station via intermediate relay robots for wireless communication. In our previous results, we confirmed that Levy walk outperformed the usual random walk for exploration strategy in real robot experiments. This paper investigated the performance of a new Levy walk generator, which is recently proposed in biology, for the targets exploration problem on robotics through a series of computer simulations and compared the performance with those for the Levy walk generator employed in our previous work. The results suggest that the search of the new Levy walk is robust for uniformly and non-uniformly distributed targets and outperforms the previous one.

ABSTRACT. Congestion frequently occurs in urban areas occupied with many pedestrians, such as airports, stations and crossings. Congestion causes many problems, leading to uncomfortable feelings and sometimes serious accidents. To counter this problem, it is necessary to model and control human flows. The ways to control two flows of people were previously studied; however, the four-way crossing phenomenon with two pairs of opposing human flows intersecting each other leads to even more congestion that is not easy to counter. In this study, we employ a continuum-model to simulate four-way crossing pedestrian flows, assuming the scramble crossing. Based on the simulated results, we introduce a method to reduce the congestion. By moving a few guide robots by a circle-trajectory in the crossing, we can avoid a dense situation. We report some preliminary results to validate the proposed method.

ABSTRACT. Boid is a simple multi-agent model of the behavior of an animal group. Boid agents communicate locally. I studied a heterogeneous boid model comprised of many agents that are divided into two types, and examined its behavior changing interaction between types of agents. In this paper, inspired by a simple ”group action”, I modified this model changing sensor area between types of agents and tuned it. The modified model generates the oscillatory pattern where groups of different type agents pump in the opposite direction.

ABSTRACT. Out-of-the-box swarm solutions powering industrial logistics will need to adapt to the tasks at hand, coordinating in a distributed manner to transport objects of different sizes. This work designs and evaluates a collective transport strategy to move large and arbitrarily shaped objects in warehouse environments. The strategy uses a decentralized recruitment and decision-making process, ensuring that sufficient robots are in place for a coordinated, safe lift and transport of the object. Results show robots having no prior knowledge about the object's size and shape were successfully able to transport them in simulation.

ABSTRACT. This paper is concerned with multi-robot exploration in environments with limited communication that is supposed to be unreliable. The communication is low bandwidth, sufficient only for sharing positions of the robots, and does not allow sharing maps of the environment. Under these constraints, we propose to address the multi-robot exploration as a decentralized task allocation to coordinate robots in the exploration mission while exchanging only their positions. The feasibility of the proposed approach has been validated in various simulated scenarios within the virtual cave circuit environments of the DARPA Subterranean Challenge. The reported results indicate the proposed approach yields shorter or competitive average longest traveled paths than the decentralized MinPos method with the allowed sharing of full environment maps. The introduced method thus represents a suitable choice for decentralized task allocation in limited communication scenarios.

ABSTRACT. This paper studies distributed formation and orientation control of multiple robots using relative measurements in local coordinate frames. The control objective is to achieve a desired formation with all robots facing a target for monitoring. To address this issue, we propose a distributed clique-based formation and orientation control law and analyze the stability of the system. Besides, the effectiveness of the proposed method is illustrated through simulations.

ABSTRACT. The nests built by social insects are complex group-level structures that emerge from interactions among individuals following simple behavioral rules. Nest patterns vary among species, and mathematical models show that this diversity can be explained by the quantitative modification of a shared set of rules. However, the comparative studies needed to test these models have not been performed. Here we compare tunnel formation in two termite species and show that differences in their branching patterns result from quantitative tuning of shared building rules. In both species, excavators transport sand particles individually from the tunnel face; when crowding prevents them from reaching the tunnel face, they choose between waiting for the tunnel to clear or beginning excavation at the sidewall. The two species differ only in the probabilities of these actions, such that the one favoring waiting reduces the number of branches. We further show that a third species independently evolved low-branched patterns using different building rules. Rather than dig individually, excavators of this species work in a bucket-brigade; in a crowded tunnel, they receive and pass back sand grains rather than excavate the sidewalls. These results elucidate the complex relationship between individual behavior and group-level patterns; in some cases, distinct behaviors can produce similar structures, but in others, the regulation of a common behavior can yield distinct patterns. The finding is parallel to the relationship between gene expression and morphology, emphasizing that evolution follows the same principle across different biological levels.

ABSTRACT. The ability to efficiently move in complex environments is a fundamental property both for animals and for robots, and the problem of locomotion and movement control is an area in which neuroscience, biomechanics, and robotics can fruitfully interact. In this talk, I will present how biorobots and numerical models can be used to explore the interplay of the four main components underlying animal locomotion, namely central pattern generators (CPGs), reflexes, descending modulation, and the musculoskeletal system. Going from lamprey to human locomotion, I will present a series of models that tend to show that the respective roles of these components have changed during evolution with a dominant role of CPGs in lamprey and salamander locomotion, and a more important role for sensory feedback and descending modulation in human locomotion. I will also present a recent project showing how robotics can provide scientific tools for paleontology. Interesting properties for robot and lower-limb exoskeleton locomotion control will finally be discussed.

ABSTRACT. Experimental testing of macroeconomic models is usually difficult, but we are attempting to break through this difficulty using ants as a model organism. Some ants form a large, spatially expansive colony where one family has multiple nests (polydomy), while in other ant species each family possesses a single nest (monodomy). Why such variation exists in nature? We compared response to heterogeneous resource distribution between monodomous and polydomous ants. A series of laboratory experiments with nests connected by tubes revealed that nests in a polydomous colony exchange complementary resources and the colony as a whole is physiologically integrated. In marked contrast, the monodomous ant kept the highest performance over five weeks even when only a nutritionally biased food was provided. This suggests that they store a large amount of nutrients in adult bodies that can be used when the outside food availability becomes poorer. The above suggests that polydomous ants and monodomous ants might adopt different strategies to heterogeneity in resource distribution. Polydomy might be a strategy to counter it spatially by extending the area of resource searching (like a global economy), whereas monodomous ants might deal with it temporarily by withstanding resource depressed periods of time (like a closed economy). Second, using polydomus ants, we tested a new hypothesis that nests are not only sharing complementary resources, but each nest tends to specialize in collecting one resource under spatially heterogeneous environments. Furthermore, we studied the rules of decision making of each nest that underlies such specialization of resource utilization and/or task specialization. Namely, we tested the comparative advantage and the absolute advantage models in trade theory. Finally, I would also like to discuss the communication mechanisms, enabling these "international division of labor”-like behaviors.