The adaptive behavior of living creatures is considered to be generated by interactions between the brain, body, and environment. However, to better understand this essence, it is important to study ...the minimalistic set of interactions between the brain, body, and environment and to extract the underlying control mechanism. Therefore, in this research, we propose a novel methodology for observing the behavior by stepwise inhibition (zombification) of the upper brain functions of living organisms. * * This article is a translation from the article: K. Osuka, “Source of Various Behaviors of Living Things that Understands from Zombification of Insects,” The 8th Conf. of Transdisciplinary Federation of Science and Technology, D-2-1, 2017 (in Japanese).
In areas inaccessible to humans, such as the lunar surface and landslide sites, there is a need for multiple autonomous mobile robot systems that can replace human workers. Robots are required to ...remove water and sediment from landslide sites such as river channel blockages as soon as possible. Conventionally, several construction machines are deployed at civil engineering sites. However, owing to the large size and weight of conventional construction equipment, it is difficult to move multiple units of construction equipment to a site, which results in significant transportation costs and time. To solve such problems, this study proposes GREEMA: growing robot by eating environmental material, which is lightweight and compact during transportation and functions by eating environmental materials once it arrives at the site. GREEMA actively takes in environmental materials, such as water and sediment, uses them as its structure, and removes them by moving itself. In this study, two types of GREEMAs were developed and experimentally verified. First, we developed a fin-type swimming robot that passively takes in water into its body using a water-absorbing polymer and forms a body to express its swimming function. Second, we constructed an arm-type robot that eats soil to increase the rigidity of its body. We discuss the results of these two experiments from the viewpoint of explicit-implicit control and describe the design theory of GREEMA.
A McKibben-type pneumatic actuator (MPA) is a soft actuator that generates tension by inflating a rubber tube with compressed air. Electropneumatic regulators are typically employed to regulate air ...pressure in MPAs. However, they are normally large in size and expensive, which are significant obstacles to the autonomous decentralized control of many MPAs in achieving various robot motions. In this study, the exerted tension of the MPA was controlled using a small solenoid valve that could be opened and closed instead of an electropneumatic regulator. To achieve this tension control, we proposed the use of a dynamic quantizer that converts continuous pressure values into discrete pressure values and controls the solenoid valve based on the discretized pressure values. The proposed method was applied to feedforward and feedback control of the exerted MPA tension under isometric conditions. Experiments on an actual device with a small solenoid valve demonstrated the effectiveness of the proposed method based on a dynamic quantizer.
In the past decades, robot navigation in an unknown environment has attracted extensive interest due to its tremendous application potential. However, most existing schemes rely on complex sensing ...systems and control systems to perceive and process the geometric and appearance information of the surrounding environment to avoid the collision, while making less use of the mechanical characteristics of the environment. In this research, in order to explore how to make a robot navigate in an unknown environment with minimal active control and minimal sensing by taking full advantage of the mechanical interactions from the environment, which is called implicit control in this study, we propose a centipede robot and its corresponding navigation scheme for navigating a 2D unknown environment without sensing information about the surrounding environment. In this scheme, the only observation input of this system is the goal direction information relative to the robot direction. Based on this scheme, we built a prototype robot and conducted navigation experiments in three environments with different levels of complexity. As a result, we obtained the navigation route map and navigation time distribution of each environment and analyzed the characteristics and applicability scenarios of the proposed navigation scheme compared to the traditional ones.
Osaka University and Komatsu Ltd. started a joint research project in 2006 as an industry-academia collaboration activity, and Komatsu established a cooperative research center on Osaka University ...campus in 2015. The center has conducted joint research to solve the problems of companies as well as independent research on remote and autonomous construction machinery. Since 2017, it has been working on “HENNA” construction equipment (“HENNA” in Japanese means “novel and innovative with unconventional thinking”) as a new research idea that combines the academic nature of Osaka University with the corporate nature of Komatsu. These research initiatives and the concept of the Cooperative Research Center (2017–present) are presented here.
This study considers a simple robot swarm navigation system based on shepherding in an environment with obstacles. Shepherding is a system in which a small number of control agents (shepherds and ...sheepdogs) indirectly guide several robots (sheep) by driving them from behind. Previous studies have predominantly focused on verifying proposed controllers based on numerical simulations and navigation experiments in well-prepared environments. However, additional shepherding experiments need to be conducted in environments with obstacles. This study aims to facilitate shepherding-type swarm robot navigation in an environment where a wall obstructs the goal. Usually, a high-end controller design is adopted for the robot to prevent it from getting trapped by obstacles. However, as the environment becomes more complex, the system design may become difficult. In contrast, this study proposes a simple shepherding navigation system based on creating and controlling “fields” to avoid obstacles. This research aims to verify whether the robot can be guided to a goal without obstacle recognition by creating an acoustic field based on the diffraction effects of sound. The proposed method modifies the previous shepherding models for sheep and shepherd robots to make them behave according to the acoustic field gradient. We demonstrate the validity of the proposed system by performing robot navigation for dog and sheep robots.
“Multi-agent systems (MAS)” have been extensively studied across various fields, including robotics, economics, biology, and computer science. A distinctive feature of these systems is the ability of ...multiple agents, each with different characteristics, to perform system-wide tasks through local bottom-up interactions. Furthermore, design and control methods for system networks based on graph theory are being developed. Recent applications of these methods include autonomous driving technology, smart grids, and understanding social systems. This special issue aims to deepen the understanding of MAS, focusing on their control and applications. It features 16 papers, including one review paper. The accepted papers cover a wide range of topics, including reinforcement learning, autonomous mobility systems, and machine learning, presenting the latest research findings on MAS. These studies provide valuable insights into various aspects and potential applications of MAS. We hope that this issue will be beneficial to our readers and contribute to the advancement of future research.
In this study, we propose a centipede-like swarm robotic system capable of utilizing “unfavorable” environmental effects such as robot–environment collisions, robot–robot collisions, signal noise, ...and signal interval, to aid navigation and exploration in 2D unknown environments. Traditional swarm robots demand complex systems to counteract “unfavorable” environmental effects, making the design of robots to handle unknown environments with theoretical infinite possibilities exceedingly challenging. In contrast, our approach does not view these “unfavorable” environmental effects as foes to be combated, but instead employs strategies like implicit control to convert them into beneficial influences on the task. This simplifies the swarm robot system, enabling navigation and exploration with only goal direction as the single input, eliminating the need for inter-robot observation, inter-robot communication and obstacle detection. Finally, we validate our system’s effectiveness through simulations in the CoppeliaSim environment, demonstrating the benefits of “unfavorable” environmental effects and the method’s universal applicability.
McKibben pneumatic actuators (MPAs) are soft actuators that exert tension by applying compressed air to expand a rubber tube. Although electro-pneumatic regulators can control air pressure, most are ...large and expensive. This study utilizes a dynamic quantizer to control the MPA with a small solenoid valve that can only open and close the valve instead of an electro-pneumatic regulator. A dynamic quantizer is one of the quantizers that converts continuous signals to discrete signals. Our previous study confirmed that tension control of MPA under isometric conditions could be realized using a dynamic quantizer. However, it is often necessary to control the length of the MPA as well as the tension of the MPA. This study implements a dynamic quantizer to control the length of the MPA with a small solenoid valve. Numerical simulations and experimental tests verify the effectiveness of the proposed method. The results of the numerical simulations and experimental tests confirmed that the length of the MPA can be controlled using the dynamic quantizer.
In recent years, research has been conducted on swarm robot systems in which multiple autonomous mobile robots cooperate to perform tasks. Swarm robot systems are expected to perform high ...functionality as a group by cooperating with each other, in spite of the limited capabilities of the individual robots. This paper explores a method of simplifying swarm robot controllers as much as possible for swarm robot navigation. If we can achieve autonomous navigation of swarm robots to a target area with minimal resource consumption, they only need to implement the task execution function in that area. This leads to lower costs for swarm robot design and more efficient system architecture design. To address the above aims, this study focuses on heterogeneity. Specifically, we introduce a navigator robot that indirectly guides swarm robots named the worker robots. Heterogeneity in this paper refers to the worker robots and the navigator robots. We design the interaction between the navigator robot and the worker robots to provide a system that guides the worker robots to the destination.
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