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An actuator for achieving the same force in both directions, and a mechanism for supporting rotary motion with the actuator are proposed. By fabricating models and performing tests, the action of the actuator mechanism, and its application on an excavator was demonstrated. Simulations on the arm-moving task performed on a conventional excavator and an excavator with the actuator mechanism show an efficiency improvement with the use of the proposed actuator mechanism, particularly when the arm is driven at low speed.

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.

McKibben pneumatic actuators (MPAs) are soft actuators that exert tension by inflating a rubber tube with compressed air. Although electropneumatic regulators can control air pressure, their cost and size limit their applications. This study employs a dynamic quantizer to control an MPA using a small solenoid valve that can only open or close, as opposed to an electropneumatic regulator. A dynamic quantizer is a type of quantizer that converts continuous signals into discrete signals. Our previous study confirmed that the tension or length control of MPA can be achieved using a dynamic quantizer. As MPA exerts force only in the direction of contraction, multiple MPAs must be combined when using them as robot actuators. This study demonstrates that control using a dynamic quantizer is feasible, even when multiple MPAs are employed. We focused on a pendulum driven by two MPAs to achieve angle-tracking control using a dynamic-quantizer-based control method. The results of numerical simulations and experimental tests confirm that the angle of the pendulum can be controlled using MPAs with a dynamic quantizer.

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.

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.

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.

The automatic generation of dynamic facial expressions to transmit the internal states of a robot, such as mood, is crucial for communication robots. In contrast, conventional methods rely on patchwork-like replaying of recorded motions, which makes it difficult to achieve adaptive smooth transitions of the facial expressions of internal states that easily fluctuate according to the internal and external circumstances of the robots. To achieve adaptive facial expressions in robots, designing and providing deep structures that dynamically generate facial movements based on the affective state of the robot is more effective than directly designing superficial facial movements. To address this issue, this paper proposes a method for automatically synthesizing complex but organized command sequences. The proposed system generated temporal control signals for each facial actuator as a linear combination of intermittently reactivating decaying waves. The forms of these waves were automatically tuned to express the internal state, such as the arousal level. We introduce a mathematical formulation of the system using arousal expression in a child-type android as an example, and demonstrate that the system can transmit different arousal levels without deteriorating human-like impressions. The experimental results support our hypothesis that appropriately tuned waveform facial movements can transmit different arousal state levels, and that such movements can be automatically generated as superimposed decaying waves.

Recently, soft actuators have gained considerable attention owing to their flexibility and high output-to-weight ratios. The McKibben pneumatic actuator (MPA), a type of soft artificial muscle, is an actuator that generates force by inflating a rubber tube with compressed air. Conventional MPAs, such as linear actuators, generate force along straight lines; hence, achieving complex movements, such as bending using a single muscle, can be challenging. In this study, we enabled bending movements in MPA by applying an elastic adhesive coating to MPA. Experimental results demonstrated that the coated MPA successfully performed bending movements. Furthermore, we confirmed that the curvature and fiber angles of the coated and uncoated surfaces changed with applied pressure, thereby indicating that the adhesive can be used to control the fiber angles and achieve the desired curvature.

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.