In this study, we propose an insect-inspired odor intake method for carrying out chemical plume tracing (CPT) in an outdoor environment and experimentally investigated the relationship between the intake state and behavioral states of search. Tracking chemical plumes is important because it facilitates the identification of an odor source. Previous studies have focused on the development of CPT algorithms to improve CPT performance. However, there is still inadequate discussion on the effect of the amount of odor acquisition, which is an important factor in determining the state of searching behavior, on CPT performance. To address this issue, we first designed and developed an insect-inspired odor-intake device. To evaluate the performance of the device, we conducted CPT experiments in an outdoor environment. An insect-inspired CPT algorithm that relies only on odor information was adopted because the purpose of this study was to evaluate the performance of the odor intake device. As a result of the outdoor CPT experiment, it was found that by setting the appropriate combination of the odor intake state and the behavioral state, certain search performances can be maintained even in highly unpredictable environments, such as outdoors. This suggests that in order to improve the CPT performance, it is important not only to improve the algorithm but also to devise an odor intake method and to combine it with the behavioral state appropriately.

In this paper, we focus on the chemical plume tracing (CPT) problem, which is a known engineering challenge. In nature, animals solve the CPT by adaptively modifying their behavior according to the environment. Therefore, we propose a CPT solution method with high engineering value by modeling the CPT algorithm of an animal. In this paper, we consider a male silkworm moth as a model. To perform CPT in a turbulent environment, the adaptive selection of the behavior plays an important role. Therefore, we performed simultaneous measurement experiments involving CPT behavior of the brain and analyzed the links between the brain's neural activity and behavioral patterns. We measured the brain's neural response in the lateral accessory lobe (LAL), which generates motion commands. We employed fuzzy inference to analyze the relationship between CPT behavior and LAL neural activity. As a result of analyzing the relationship between CPT behavior and LAL, we found that the moth modulates the behavior of the state transition probability depending on the odor frequency. We modeled the obtained phenomenon and verified its effectiveness through a constructive method. As a result, the search performance was improved compared to the conventional moth algorithm.

To realize an autonomous odor source localization robot, we focused on the adaptability of an insect's brain to compensate for rotational disturbances during odor source searching behavior. We manipulated motor outputs to control the sensory feedback of an insect using a brain-machine hybrid system. This system is composed of an insect's head and a two-wheeled mobile robot. The velocity of the robot is proportional to neural activities descending from an insect brain. We successfully manipulated the behavior of the robot. In disturbance experiments, insects responded to given rotational disturbances by modifying their neural activities to make compensative angular velocity. We assumed this control system of the compensation as an output-error model. We calculated the parameters under different motor gains to reveal it as an adaptive controller. We propose that an insect has its appropriate angular velocity during odor source localization, and performed simulation experiments involving an odor source searching agent and odor distribution environment. We calculated the cost for odor source localization by changing the angular velocity of the agent, and found that it had the minimum value.

We have created a brain-machine hybrid system (BMHS) which is able to solve the chemical plume tracking (CPT) problem using the brain of the male silkworm moth. The purpose of the system is to investigate adaptability which results from interactions between brain, body, and environment. In this paper, we describe a BMHS architecture and experiments to verify that the behavior of the BMHS is similar to that of a silkworm moth. The BMHS is a kind of cyborg system in which the body of a living being is replaced by a mobile robot and the organism's brain is used to control the robot. The artificial body is controlled by motor commands for the original body that are extracted from a signal recorded from the brain. For that purpose, a small measurement system to record signals was created and a method to reconstruct the motor commands from the signals was established. We demonstrate that the BMHS can behave like a silkworm moth. We compared the trajectories of moths with the trajectories of the BMHS incorporating the same individual moths. Through the experiments we confirmed that the system can solve the CPT problem. Our system has the potential to reveal principles of adaptability in silkworm moth behavior.

Navigation systems based on animal behavior have attracted considerable attention in the past few years. Navigation systems using artificial pheromones have not been extensively developed. Therefore, this paper presents a model for realizing an artificial pheromone system by using data carriers and autonomous robots. By introducing an artificial pheromone system composed of data carriers and autonomous robots, a robotics system creates a potential field for navigation. First, we develop pheromone density in a discrete nominal model. Then, we extend the model to deal with a random layout that is suitable for real conditions of data carriers. For demonstration of the effectiveness of our proposed model, computer simulations and hardware implementations are performed. The artificial pheromone potential field constructed using our proposed model can be used for the navigation of autonomous robots.

In recent research, the morphological effect is widely discussed from walking to the Internet, and its mechanism for generating the functionality has been discovered. In this paper, a module that employs the structural effect for controlling behavior is constructed using coupled nonuniform van der Pol oscillators. We first examine the synchrony of two types of oscillators focusing on number; then, an oscillator module that changes its synchrony from structural disposition is constructed. Oscillators are mutually arranged on a ring-shaped network, and an additional connection is used for transformation. The stability of this system is also discussed, and finally, the procedure for designing this structure-sensitive module using more than three types of oscillators is described.

Insects have small brains, but their behavior is highly adaptive; this leads us to conclude that their brains possess a simple adaptation mechanism. This paper focuses on the pheromone processing of crickets, varying their aggression depending on their global neural connection, and proposes a behavior selection mechanism that can be controlled by network transformation. The controller is composed of an oscillator network, and its behavior is decided by the synchrony of organic oscillations. Furthermore, every network component corresponds to a certain brain module. A model is realized by using an analog circuit, and it is applied to a simple robot that displays the behavior of a real insect.

In this paper, we propose and implement a formation control algorithm for a mobile robot group. Although obstacle avoidance is a highly essential function, it is not compatible with maintaining a formation. In previous studies, robots often switched their motion algorithms. However, there no concrete criteria exists for such decisions. In this paper, we employ the synchronization of nonlinear oscillators that communicate with each other. By using sensor signals, we vary the phase gaps among the oscillators. According to these phase gaps, we change gains to form a group in order to avoid obstacles. We have implemented the proposed system using actual robotic systems and have demonstrated its feasibility

In this paper, we propose an autonomous multiagent system composed of an intelligent environment (static agents) and mobile agents (robots). We focus on procedure that autonomous mobile agents construct feasible paths. In the system, not a mobile agent but an environment gathers information and makes decisions. We formulate the optimal condition and an optimization algorithm by means of media agents that play the role of communication links between static agents. We also formulate the appropriate ratio of the media agents in the system. We discuss the efficiency of the system by results of simulations.

In this paper, we focus on the procedure whereby an autonomous multiple robot system constructs feasible paths. We formulate optimal solutions in the following two cases; (i) a robot makes the decision by itself, (ii) an environment (or specific locations in an environment) gathers information and makes suggestions. We also propose learning algorithms for appropriate path construction in both cases. Then we discuss the efficiency of the two cases based on optimal solutions and learning results of simulations.

We propose information assistance for a victim search system in a rescue activity. We have developed an intelligent data carrier system (IDC) that provides the environment with information storage, sensing, and processing functionality. Each IDC unit has its own CPU, memory and radio communication module. We have incorporated the auditory functionality into IDC units and applied them to rescue activity support. IDC units attached in buildings are activated by broadcast of a wake-up signal, and then they repeat calling to victims and recording their answers independently. Rescue parties perform effectively by seeking records of victims. We have also built an autonomous dispatch system of autonomous robots based on the information obtained by the IDC system.

In this paper, we propose a device for cooperation of multiple autonomous mobile robots. A device which enables local communication, named "intelligent data carrier (IDC)", is proposed. In this paper, we propose an algorithm to improve efficiency of iterative transportation tasks by autonomous mobile robots. An autonomous mobile robot gives name of its latest visited destination to an IDC which is located on a junction in a work area. An IDC summarizes the information from robots and tells a direction that it effects best way to a destination which a robot wants to go. By the proposed algorithm and system, mobile robots construct information of navigation and improve the efficiency of a task automatically. We verified the effect of the proposed algorithm by simulations and experiments.

In this paper, we propose a heterogeneous robot group for cooperative task execution. The "heterogeneous" robot group is composed of robots which have different motion algorithms. In this paper, we investigate behavior of the heterogeneous robot groups by simulations of multi-agent traveling salesman problem, which we hardly solve by centralized algorithms. Then we propose an algorithm, based on reinforcement learning, to adapt mixture ratio of robots driven by different algorithms. We verify the efficiency of the autonomous heterogeneous robot group by simulations.

We propose an algorithm for unforeseen obstacle avoidance by an autonomous sweeping robot. Sweeping means a motion that a robot covers a 2-dimensional area. When a mobile robot finds an unforeseen obstacle, it not only has to avoid collision but also sweep whole area including around the obstacle. In the proposed algorithm, a robot determines local area where path for sweeping should be arranged according to its limited sensing ability. By connecting the paths inside and outside the local area, the robot obtains a new total path. The local path re-planning saves heavy calculation to generate whole path again at online.

Service robots are extensively installed with end-effectors, which require high energy to achieve a specific task. Robots require high-power energy sources that can meet several goals simultaneously. Given the technology of today a battery-driven robot cannot work for long on a single charge. To develop a new powerful battery technology may take many years. In this paper we present a dual-energized scheme called Hybrid Power Supply (HYPOS) that integrates the function of batteries and household electric system to supply power to a robot. This technique can be realized by the existing technology and is applicable to a variety of indoor applications. The paper includes the description of the prototype robot and the experiments that illustrate the effectiveness and practicalness of this proposed system.

In this paper, we propose an off-line planning algorithm for cooperative tasks of multiple mobile robots. Sweeping means a motion that a robot covers a 2-dimensional area by its effector. Sweeping of a whole work area is fundamental and essential task of mobile robots. For efficient cooperation, setting appropriate burden onto each robot is very important because interference of robots and overlaps of their effecters make efficiency low. The cost of sweeping depends on both sweeping ability of a robot and a shape of a work area to be swept. Evaluation and distribution of the cost are most important issues. In the proposed algorithm, the cost is evaluated by means of length on which robot should move. We introduce both edges of the configuration space and Voronoi diagram so as to compute paths in the whole area. We generate the a tour for traversing all the paths by applying the algorithm of the Chinese Postman Problem. According to the cost evaluation, appropriate paths of the tour are assigned to each robot. The efficiency of the proposed algorithm is verified by simulations and an experiment.

In this paper, we propose an off-line planning algorithm for cooperative tasks of multiple mobile robots. Sweeping means a motion that a robot covers a 2-dimensional area by its effector. Sweeping of a whole work area is fundamental and essential task of mobile robots. It is more effective if a robot can move an obstacle during a sweeping task as if we clean our room with relocating chairs. We can also consider that this is the simplest task which includes both point-to-point motion and sweeping. We model sweeping and relocation, and propose an algorithm to find appropriate path for robot and way of relocation of each obstacle. We apply the LT graph to solve the problem, which describes both motions of robots and blockades by obstacles in path-time space. We verify the efficiency of the algorithm through simulations and experiments.

This paper deals with a motion planning of mobile robots during the cooperative transport of a large abject by a group of multiple mobile robots (a robot group). In spite of the complexity of the relationship between the several kinds of requirements for this problem, motion planning should be done in real time according to each robot's torque limit to apply its force to the object. Based on the algorithm of Ota et al. (1995), the authors propose the following approach: (1) derive handling force applied to the object by each robot, and (2) determine the role for each robot (to handle the object or to regrasp it) by each robot's torque limit and optimization of a penalty index indicating performance for obstacle avoidance, stable grasping, and reduction of force. Effectiveness of the proposed method is verified by a transferring simulation.

One of the major emerging problems of distributed mobile robotic system is what kind of inter-robot communication to use, because of increasing robots integrated in the system. This paper aims to give an analytical view of this issue. The efficiency of local and global communication is compared based on the analysis of information transmission time to multiple robots. We will show that local communication is effective in environments where cooperative tasks are executed by multiple mobile robots in distributed fashion.

The authors aim at grasping and handling a large object by cooperating multiple mobile robots with various sizes, moving cost, and load capacity. In this paper the authors focus on the problems of deciding an appropriate grasping arrangement before handling operations. The authors propose this method to avoid bad situations, such as making an object fall down, or some robots overloaded in grasping and handling. The algorithm proposed includes two optimization problems; one is the "decision of initial robot arrangement," the other is the "decision of final robot arrangement." The difference between these optimizations is that the mass center of the object is recognized or not. The penalty index is defined to minimize the energy the system consumes and to maximize an index of stability. The authors have confirmed that the robots moved to the optimal arrangements in computer simulations and experiments.

When many mobile robots should achieve cooperation, a local communication system is considered appropriate from the standpoint of the cost and capacity of communication. This paper presents the optimization of the efficiency of local communication in environments where many mobile robots send out information stochastically. The optimal communication area is derived by minimizing the transmission waiting time calculated using the probability of successful information transmission. Computer simulations have been undertaken to verify the analytical results.

Proposes an algorithm of dividing a work area into small pieces in order to make multiple mobile robots cooperate efficiently. Searching of a whole work area is the most fundamental and the most essential task of mobile robots. The authors expect that the cost of searching is shared by cooperation of multiple robots. In the proposed algorithm, searching motions of robots are represented by paths. Both edges of the configuration space and the Voronoi diagram are introduced so as to compute paths in the whole area. The authors generate a tour of the paths to traverse all the paths using the algorithm of the Chinese postman problem. The cost is estimated as the total length of the paths. By means of the cost evaluation, the appropriate paths are assigned to each robot. The efficiency of the proposed algorithm is verified by simulations.

Local communication system is considered appropriate when many mobile robots should achieve cooperation, from the standpoint of cost and capacity of communication. This paper presents a design method of the optimal communication range for efficient local communication system. The analyses of optimization are made by minimizing the information transition time, first in the case of transmission to an arbitrary robot, and next, to multiple robots. Computer simulations have been undertaken to verify the analytical results.

A motion planning method for robot groups is presented. First, groups are classified into a group on common partnership (P-group) and a group in shape (cluster) based on types of common factors among members of the same group. The concept of cohesion is proposed to express changeability of clusters. Next, a motion planning method with dynamic grouping, which changes number of cluster in the group based on cohesion, is presented. The approach is implemented using the virtual impedance method. The effectiveness of the method is verified by simulation results.