ABSTRACT. The last few years have seen significant progress in our understanding of how one should structure multi-robot systems. New control, coordination, and communication strategies have emerged and, in this talk, we discuss some of these developments. Inspiration will be drawn from naturally occurring, self-organizing systems and we will show how one can go, in a provably correct manner, from global, team-level specifications to local coordination rules for achieving and maintaining formations, area coverage, and biologically inspired swarming behaviors.

ABSTRACT. Social insects rely heavily on pheromone communication to maintain their sociality. Their reproductive system is regulated by queen pheromone. We identified a queen-produced volatile chemical that inhibits the differentiation of new neotenic reproductives in a termite. In contrast to this top-down control, social insects also rely on self-organizing rules to perform social labor, as members communicate with neighbors to make consensual decisions. By using shelter-tube construction and egg piling behavior as model systems, we are identifying the algorithm of collective building and decision making system in termites.

ABSTRACT. This paper introduces a design method of multi-robot systems for motion-coordination based on gradient systems. The gradient systems are systems where the time derivative of the state is equal to the gradient of a function. In the design method, we construct a communication structure among robots and controllers in those so that the resulting feedback system is the gradient system for a function representing the achievement degree of a task. This is a powerful tool to achieve multi-robot coordination because the convergence analysis is easy due to a property of the gradient systems.

ABSTRACT. Patients employ orthoses for the lower limbs to gain support for movements they themselves could perform not at all, or only with difficulties. The combination of patient-abilities and chosen controller determines suitable devices. We present a model based controller, which can be individualised by gait samples. It allows continuous control over the whole gait cycle based on the tracking of gait progress and makes no assumption on the patient's abilities. We conclude by analysing the evenness and continuity of the presented gait progress tracking.

ABSTRACT. Among a large number of possible gaits, only particular patterns appear in insect locomotion and insects transit the gaits continuously depending on speed in contrast to the distinct gaits in some quadrupeds. The mechanism of how they choose these particular gaits and change them continuously is still unclear. Recent studies in biology suggest that a functional motor output during walking is formed by the interaction between central pattern generators (CPGs) and sensory feedbacks. In this paper, we investigate the dynamics of a hexapod robot model whose legs are driven by distributed oscillators with a local sensory feedback from neuromechanical point of view. This feedback changes the oscillation period of the oscillator depending solely on the timing of the contact between the foot and the ground. The results of dynamic simulations and real robot experiments show that due to the local sensory feedback the robot produces continuous stable gaits depending on the locomotion speed as a result of self-organization, one of which are similar to those of insects. These results reveal that the neuromechanical interaction induced by the local sensory feedback plays an important role in generating the gaits of insects at low speed, which is consistent with the suggestion from the physiological study.

ABSTRACT. Human walking emerges from an intricate interaction of nervous and musculoskeletal systems. Inspired by this principle, we integrate neural control and muscle-like mechanisms to achieve neuromechanical control of the biped robot RunBot. As a result, the neuromechanical controller enables RunBot to perform more human-like walking and reduce impact force during walking, compared to original neural control. Moreover, it also generates adaptive joint motions of RunBot; thereby allowing it to deal with different terrains.

ABSTRACT. Recently, there has been extensive research on robot control using self-position estimation. Simultaneous Localization And Mapping (SLAM) is one approach to self-positioning estimation. In SLAM, robots use both autonomous position information from internal sensors and data from external landmarks. SLAM can improve the accuracy of position estimation with a large number of landmarks, but it involves a degree of uncertainty and has a high computational cost, because it requires detection and recognition of landmarks through image processing. To overcome this problem, we propose a new method called Generalized Measuring Worm Algorithm which involving the creation of maps and the measurement of position using multi cooperating robots that serve as moving landmarks for each other. This makes it possible to solve problems of uncertainty and computational cost with two-dimensional markers, because a robot needs to find only a simple two-dimensional marker, rather than feature-points landmarks. In the proposed method, the robots have a two-dimensional marker of known shape and size and have a camera kept at the front of the robots sensing the markers to determine distance. The robots use this information to estimate each other’s positions and to control movement. To test the method experimentally, we used two real robots in an indoor environment. The result of the experiment revealed that the distance measurement and control error could be reduced to less than 3%.

ABSTRACT. In population-based optimization algorithms (POAs) such as particle swarm ptimization (PSO), if landscape modality of an objective function can be identified, strategies of the POAs can be selected properly. We have proposed a method that estimates the landscape modality by sampling some points, but the method needs additional functional evaluations for the sampling points. In this study, a new estimation method using a proximity graph, which does not need additional evaluations, is proposed. A proper strategy is selected according to the landscape modality: The gbest model is selected in unimodal landscape and the lbest model is selected in multimodal landscape. Also, two mutation operations for unimodal and multimodal landscapes are proposed to update the worst solution. The advantage of the proposed method is shown by solving various problems including unimodal and multimodal problems and by comparing the results of the proposed method with those of the gbest and lbest model of PSO.

ABSTRACT. The objective of our study is to design a swarm. We have developed a framework to design self-organizing, self-reconfigurable robotic systems, based on the algorithm of a multi-agent model, Swarm Chemistry, proposed by Sayama. The framework optimizes the control parameters, called recipes, subject to the given primitive tasks. Optimal recipes are heuristically searched, according to the performance scores measuring how well the task was achieved. This paper reports the results of numerical experiments for three new simple task models. The swarms could evolutionarily grow to complex behaviors, resulting in some spatiotemporal patterns to cope with difficult tasks. The task models could be interpreted as a variety of real-world problems like disaster prevention, geographical survey, subsea exploration, performed by autonomous swarm robots.

ABSTRACT. In this paper, we consider a novel Voronoi coverage algorithm with the feedback of velocity of centroids. We show that a multi-agent system achieves the centroidal Voronoi coverage by the proposed coverage algorithm based on the analysis with a Lyapunov-like function. We also show that the convergence to the centroidal Voronoi coverage by the proposed algorithm is faster than that by the existing coverage algorithm through simulation experiments.

ABSTRACT. This paper deals with a seeking problem for multiple source by swarm robots. By using swarm robots, it is expected to find multiple sources at once. In this paper, we design a decentralized controller to spread the robots out on the multiple sources instead of gathering on one source.

ABSTRACT. We study disease spread over a time-varying network modeled by Markov processes. Using the framework of geometric programming, we propose an efficient algorithm to design the cost-optimal strategy for distributing protection resources throughout the agents in the network to eradicate epidemic outbreak, as well as to attenuate the effect of infection from the outside of the network. The obtained result is illustrated with a numerical simulation.

ABSTRACT. This paper addresses the structural bistability of boolean networks. We derive a necessary and sufficient condition for boolean networks with a 8-shaped network structure to be structurally bistable.

ABSTRACT. We present a system that combines human creativity and imagination with artificial evolution in order to produce efficient gaits for prespecified morphologies of soft-bodied robots. A designer is free to propose a shape for the robot for which a control mechanism is then found automatically. We assume that the animats are made of soft material capable of locally contracting and expanding and represent them as 2-D triangular meshes. Animat motion is simulated in a physics engine as a spring-mass system with pressurized body regions. Movement is possible owing to evolved patterns of contraction amplitudes, frequencies and phase shifts, with each body region capable of maintaining its own, independent rhythm of contractions. We analyze evolved gait controllers for terrestrial and aquatic environments for different hand-drawn morphologies and investigate a scenario in which evolution has to combine active material with a passively elastic one to produce energy and resource efficient robots. Our results show how evolving distributed actuation mechanism is a powerful method for producing gaits for elastic bodies that could find its applications in the emerging field of soft-robotics or as a method of automatic animation of video game characters.

ABSTRACT. Swarm robotics has both an engineering as well as a scientific nature. On the one hand, it studies how to design flexible, robust, and scalable collective behaviors to solve real-world problems in large, unstructured environments. On the other hand, it is also useful to biologists to study the proximate mechanisms employed by social species to achieve the astonishing levels of collective organization that are often observed in nature. Evolutionary swarm robotics has a similar double nature. On the one hand, the use of evolutionary computation techniques is proposed as a solution to the design problem, that is, to decompose the collective-level goal into the local behaviors of the robots. On the other hand, studying evolutionary robotics scenarios can be very useful to biologists to understand the ultimate causes and factors that promote the evolution of specific types of collective organization in nature.

In this paper, our goal is to use an evolutionary swarm robotics scenario to answer questions related to the evolution of recruitment strategies in social insects. We consider a foraging scenario in which objects are distributed in the environment according to specific distributions. We show that the way food is distributed in the environment has a significant influence on whether and which recruitment strategies emerge through the evolutionary process. The results of this paper are therefore useful both to advance our understanding on the evolutionary causes of recruitment in biological systems, as well as to hint to engineers the requirements to evolve complex coordination strategies.

ABSTRACT. Underwater snake robots constitute a bio-inspired solution within underwater robotics. Increasing the motion efficiency in terms of the forward speed by improving the locomotion methods is a key issue for underwater robots. Furthermore, the energy efficiency is one of the main challenges for long-term autonomy of these systems. In this study, we will consider both these two aspects of efficiency, which in some cases can be conflicting. To this end, we formulate a multi-objective optimization problem to minimize power consumption and maximize forward velocity. In particular, the optimal values of the gait parameters for different motion patterns are calculated in the presence of trade-offs between power consumption and velocity. As is the case with all multi-objective optimization problems, the solution is not a single point but rather a set of points. We present a weighted-sum method to combine power consumption and forward velocity optimization problems. Particle Swarm Optimization (PSO) is applied to obtain optimal gait parameters for different weighting factors. \textit{Trade-off curves} or \textit{Pareto fronts} are illustrated in a power consumption--forward velocity plane for both lateral and eel-like motion pattern. They give information on objective trade-offs and can show how improving power consumption is related to deteriorating the forward velocity along the trade-off curve. Therefore, decision makers can specify the preferred Pareto optimal point along the trade-off curve. Moreover, we address some interesting questions regarding the optimal gait parameters, which is a significant issue for the control of underwater snake robots in the future.

ABSTRACT. Nest excavation in social insects is an integral part of a colony’s life cycle. Soil-dwelling colonies build complex systems of narrow underground chambers and tunnels spanning for thousands of insect body lengths below the ground. The nest excavation is laborious, thus, performed by multiple animals simultaneously and is governed by local interactions of the workers with environment and other workers. The costs and benefits of such system are poorly investigated, mainly due to the complexity of the biological system and the lack of experimentalist control on animal behavior. To address this challenge we designed and built groups of robotic excavators, capable of performing days of autonomous tunnel excavation in a model cohesive media. The excavator behavior was governed by a simple set of rules triggered by the interactions with the surrounding environment. In the experiments we have tested the effect of the tunnel width and the size of the excavating group on the rate of the tunnel growth and the energetic costs of excavation for individual workers. The experimental data showed that in sufficiently wide tunnels the increase in the size of the excavating group had a positive effect on the tunnel excavation rates without significant increase in the energy consumption per robot. The decrease in the tunnel width resulted in the decrease in the tunnel excavation rates and increase in the energetic costs of excavation per robot. We attribute this effect to the emergence of multiple interactions (jams) between excavating robots in the confined spaces. Although the jams were successfully resolved based on local mechanical interactions of the robots in the tunnel, their presence slowed the excavation down appreciably. The duration of jams was longer in the systems with higher number of robots or narrower tunnels. We expect that the proposed robotic system may become the first step towards the universal reprogrammable platform to investigate the behavior of social insects in the confined spaces.

ABSTRACT. Schooling behavior by squid can be defined as one of social behaviors, however, its details have not been well documented. Through the series of surveys, we were successful to uncover by field and laboratory observations structure and function of school formed by squid (Sepioteuthis lessoniana). In this paper, we review our observations including ontogeny of schooling behavior, types of schooling behavior, social network of school and defensive and offensive function of school. We also discuss about genetic background of school members, which might relate variation of schooling behavior.

ABSTRACT. The swarm migration dynamics of epithelial cells in biological tissues loosely resemble those of flocks of sheep. Inspired by how sheepdogs can control sheep, we previously developed a bioelectric ‘sheepdog’ that allowed us to herd epithelial cells in living tissue. In this work, we explore how this approach allows for a new kind of tissue engineering paradigm based on ‘swarm engineering’ where we develop rules and tools to control cellular swarming.

ABSTRACT. The social species show a number of different varieties of swarm behaviors. However, it is not clear if the swarm behaviors formed by the same species are different and if the styles of swarm behaviors are dynamic. In this paper, we use a convolutional neural network to classify the differences of swarm behaviors formed by guppies. Our results show that the swarm behaviors formed by the different group can be classified and that the wholeness of the swarm behavior still remains after 6 hours.

ABSTRACT. Self-organizing robots achieve complex operations, cooperating with each other. A famous example is Kilobot, which moves via vibration motors and communicates with each other via infrared communication. For the Kilobot, this paper proposes a new formation control system based on switching role. In this study, infrared communications between robots are regarded as pheromone communications like insects. Each robot has two roles: Marker and Mover. Furthermore, robots have their priority which depends on their own ID. Information exchange including two roles and their priority enables each robot to switch their role and decide their action. These features are implemented into each robot as four simple functions. This paper demonstrates the effectiveness of the proposed system by performing two types of formation control: the formation shaping and the formation moving by inchworm movement.

ABSTRACT. This paper considers formation control of snake robots. In particular, based on a simplified model of snake robots, and using the method of virtual holonomic constraints, we derive a control law for each robot in the formation, which controls the body shape of the robot to a desired gait pattern defined by some pre-specified constraint functions. These constraint functions are dynamic in that they depend on the state variables of two compensators which are used to control the orientation and planar position of the robot, making this a dynamic maneuvering control scheme. Furthermore, using a formation control strategy we make the multi-agent system converge to and keep a desired geometric formation, and make the formation follow a desired straight line path with a given speed profile. Simulation results are presented which validate the theoretical approach.

ABSTRACT. We focus on the control of heterogeneous swarms of agents that evolve in a random environment. Control is achieved by introducing special agents: leader and infiltrated (shill) agents. A refined distinction is made between hidden and apparent controlling agents. For each case, we provide an analytically solvable example of swarm dynamics.

ABSTRACT. In this paper, stability of gaits in a rimless wheel with telescopic legs is investigated. The equation of motion of the rimless wheel during stance phase is derived and linearized. Output following control is introduced to generate the steady gaits. Two evaluation methods for the stability of the generated gaits are proposed. Each method evaluates the stability of the gaits based on the state error transition from steady gaits. One evaluates derives the transition function of the state error from the linearized equation of motion of the rimless wheel during the stance phase. Another derives the transition function based on the balance between the input energy by actuators and dissipated energy at heel strike. The transition functions are calculated by two methods for the rimless wheel and the results are compared.

ABSTRACT. This paper investigates the possibility of a stable passive compass gait sliding on a gentle slope using a novel biped robot model. First, we introduce a model of a planar compass-like biped robot that slides on a rigid downhill using small passive rollers attached to the end-position of the leg frames. The generated walking motion is expected to be similar to that of the compass-like biped robot sliding on a slippery downhill. Second, we numerically show that a stable passive compass gait can be generated with suitable system parameters, and that the joint friction force of the rollers produces a gripping effect for stabilization of the contact position with the ground. Furthermore, we conduct parametric study to observe the changes in gait descriptors with respect to the frictional coefficient.

ABSTRACT. In this research we mainly discuss two problems on limit cycle walking. One is the posture of the limit-cycle walker at impact, and the other is the walking control with visual information of the rough terrain in front of the walker. We introduce a 4-DOF kneed bipedal walker which can exert input torques on the stance-knee, swing-knee, and the hip joint to control the relative joint angles. We assume that the walker determines the landing position of the swing leg beforehand based on the visual perception, and keeps its posture similar to the case of level walking. By using mathematical method, we discuss the optimality of the control that human does on uneven ground while leaning the upper body and bending the knee joint from the viewpoint of energy efficiency.

ABSTRACT. Reynolds’s boid model (1987) is one of the first models to successfully produce swarming behavior. However, the size of the swarms was limited to a few hundred individuals. The present study is reformulated based on the original model to simulate the swarm size up to 500,000 individuals by utilizing the GPGPU technique. The preliminary study reports a qualitative change in swarm formation in larger swarms. We focused on a particular set of parameters that enables complex swarming behavior and showed: (i) a new classification of swarm groups are tested, (ii) a correlation strength gradually increases as the size of swarm increases, (iii) 10 percent of the members are exchanged but the size of the swarm is kept constant as a large swarm, and (iv) the maximum size of the swarm grows with a power law as a function of the system size.

ABSTRACT. "It brings out the animal in us" is often heard, when speaking of unaltruistic behavior. Frans de Waal has argued against a "veneer theory" of one of humanitys most valued traits: morality. It has been proposed that morality emerges as a result of a system of evolutionary processes, giving rise to social altruistic instincts. Traditional research has been arguing that fully-fledged cognitive systems were required to give each individual its autonomy. In this paper, we propose that a simple sense of morality can evolve from swarms of agents picking actions such that they are viable to the survival of the whole group. In order to illustrate the emergence of a moral sense within a community of individuals, we use an asynchronous evolutionary model, simulating populations of simulated agents performing a foraging task on a two-dimensional map. We discuss the morality of each emergent behavior within each population, then subsequently analyze several cases of interactions between different evolved foraging strategies, which we argue bring some insight on the concept of morality out of a group, or across species. This preliminary study brings a new perspective on the way morality can be measured in a population, corroborating the argument in which morality can be defined not only in highly cognitive species, but across all levels of complexity in life.

ABSTRACT. This paper describes a methodology to construct a dynamic structure by the interaction between semi-active blocks and simple robots. The block is intelligent enough to have a rule set and a counter value, and communicates with next blocks based on the rule set and counter value. Each robot just loads or unloads the block based on a simple algorithm. The structure is formed by growing the chain of the blocks controlling its direction by themselves. Its growth direction is determined by the rule set and the counter value. As the formed structure is dynamic, it has a potential to be fault-tolerant or to be adaptive for environmental changes.

ABSTRACT. This paper proposes a formation control algorithm for a multi-UAV(Unmanned Aerial Vehicle) system by using LMI(Linear Matrix Inequality) conditions. First, we show a linearized model of UAVs like quadrotors, and then, we introduce a formation control algorithm based on a consensus algorithm, a leader-follower structure, graph theory and Lyapunov stability theorem for a liner system. Second, we propose the control algorithm using Lyapunov theorem and LMI conditions in the case of intermittent communication. Then, the stability of the proposed control algorithm is shown even when some network links are disconnected. Finally, simulation results show the effectiveness of the proposed control.

ABSTRACT. In this paper, we propose a new control method which realizes ``well-organized crossing motion'' of multiple swarms of robots. Although there are several researches which realize crossing motion of multiple swarms of robots without collision, the transient state is not considered. To realize ``well-organized crossing motion'', we define what ``well-organized crossing'' is in this study, and then propose the crossing motion planning method which consists of an offline path planning, an online follow-up control and online collision avoidance. Especially, in the offline path planning, which is based on model predictive control, a trajectory with no disorder of the formation is generated. Furthermore we show the validity of the proposed method by some experimental results.

ABSTRACT. In this paper, swarm robot system to be able to move autonomously with avoiding obstacle is conducted. The swarm robot system consisted on one leader robot and two chaser robots by autonomous wheeled movement robot is treated. Then the authors propose that the leader robot can move with avoiding the obstacles by optimal navigation control method corresponding for nonlinearity constrain condition and in case of different from input variable number and output variable number. And the chaser robot can run after the leader robot by using autonomous optimal navigation control way such as the relatively position between the leader robot and chaser robot is converged to fix position all the time. To verify the effectiveness of proposing autonomous flocking control system for swarm robot system, two case experiment of swarm robot system is executed and obtained the result is evaluated.

ABSTRACT. One of the methods known to stabilize a passive dynamic walk is to restrict a hip joint angle. The hip restriction method effects as resetting the walking dynamics every time at the beginning of the walk. A Constraining Foot Shape is known to give the same effect by a more compact configuration. However, it was not clear how much this dynamics resetting effect will be given for a specific design parameter such as a length of the foot. This paper shows a numerical approach for this. Firstly, we show a dynamics of walking by 2D stick model with foot length. This is realized by considering a support point exchange effect. Secondly, we show a simulation results by this model. From this, we show that a longer foot will give a more strong effect of resetting walking dynamics. Finally, we demonstrate the validity of this model by making an actual hardware of 2D stick model with foot length. In this model, a scuffing effect was avoided by using landing islands on a slope.

ABSTRACT. This paper is concerned with a gait transition from an active walking to a passive one by an input and parameter optimization technique of Hamiltonian systems. First, a continuous-time dynamics of a passive walking/running robot between the touchdown and lift-off is considered as a Hamiltonian system. Then, the control input and some robot parameters, such as the mass, inertia, link length and so on, are optimized by using learning optimal control of Hamiltonian systems, which has been developed by the authors. This method allows one to simultaneously obtain an optimal feedforward input and optimal parameters, which (at least locally) minimize a given cost function. The main advantage is that the precise model of the dynamics of the plant system is not required by using the symmetric property of Hamiltonian systems, called variational symmetry. We formulate an optimal gait generation scheme via the learning optimal control, where the robot keeps walking and the gait is optimized with respect to the control input. As a result, a gait transition from an active walking to a passive one is achieved.

ABSTRACT. This paper studies the control of quadrupedal bounding in the presence of torso flexibility and non-trivial leg inertia, and it proposes a method for speed transitioning based on the sequential composition of locally stable bounding gaits corresponding to different running speeds. First, periodic bounding motions are generated simply by positioning the legs during flight via suitable (virtual) holonomic constraints that are imposed on the evolution of the leg angles; at this stage, no control effort is developed on legs that are in contact with ground, resulting in efficient, nearly passive, bounding gaits. The resulting motions are stabilized by a hybrid control law which coordinates the movement of the torso and the legs in continuous time, and updates the leg touchdown angles in an event-based fashion. Finally, through sums-of-squares programming, formally verified estimates of the domain of attraction of stable fixed points are used to realize speed transitions by switching among different bounding gaits in a sequential fashion.

ABSTRACT. This paper mathematically studies the impact of the time delay on the energy efficiency by an active combined rimless wheel (CRW) model driven by the discrete-time control system. The time-delay control system is simplified and proposed, and the no-delay control system is developed to make comparison. First, the mathematical analysis of the control input of the time-delay control system is studied for generating the same stable walking speeds of the no-delay control system, and the function between the two control inputs is derived. Second, the energy efficiencies of two control systems are thus analysed when the two control systems are at the same stable walking speeds. As a result, the time-delay control system has a lower energy efficiency than the no-delay control system when they are at the same stable walking speeds and the control inputs are positive. Finally, the conclusion is verified by numerical simulations.

ABSTRACT. By constituting an automatically measuring system of foraging activity of ants using tiny RFID chips, we obtained a long-time individual-scale foraging statistics of a colony of Camponotus japonicus. The analysis of the data basically supports the previously supposed mechanism of task allocation known as response threshold dynamics, whereas is also indicates that a drastic change of the hierarchy of foraging activity may take place in certain situations. These outcomes require us to establish a more elaborated model for task allocation of ants than previous ones.

ABSTRACT. Birds are frequently vocal. Monitoring their songs and calls has provided much useful information about their ecology and behavior. Recording bird songs and locations can be resource intensive, frequently requiring two or more observers, causing considerable disturbance and possible only for short times. Passive arrays of acoustic sensors offers the possibility of greatly increasing our ability to monitor bird activity. The desirability of such arrays is obvious: they are less intrusive, can monitor continuously over long periods, permit collaboration which enables better localization, provide fault tolerance and facilitate sharing to optimize scarce resources. That the interest has been increasing so much lately is in large part because we are now at the point where the promise of such arrays is realizeable with current or reasonably anticipated technologies. Controlling collaborative arrays can be difficult. Engineered solutions are sometimes available, but they are often brittle and appropriate only for ideal environments. We would like our systems to be: robust, in that they can handle changing environments or agents and are untroubled by occasionally wrong or noisy messages; adaptive in that they can learn to deal with unanticipated source or events, form new concepts and communicate in languages that are specialized for particular agents; and finally, they should be self-configuring, to deal with changing situations and goals. After reviewing research employing sensor arrays by others to monitor bird behavior, we will describe research in our laboratory. Our focus will be on the construction of such systems, especially how such arrays can extract information from the environment and communicate to arrive at a collective understanding of their region and events occurring there.