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This paper describes the development of an in-pipe inspection robot system designed for large-diameter water pipes. The robot is equipped with a Magnetic Flux Leakage (MFL) sensor module. The robot system is intended for pipes with diameters ranging from 900 mm to 1200 mm. The structure of the in-pipe inspection robot consists of the front and rear driving parts, with the inspection module located centrally. The robot is powered by 22 motors, including eight wheels with motors positioned at both the bottom and the top for propulsion. To ensure that the robot's center aligns with that of the pipeline during operation, lifting units have been incorporated. The robot is equipped with cameras and LiDAR sensors at the front and rear to monitor the internal environment of the pipeline. Pipeline inspection is conducted using the MFL inspection modules, and the robot's driving mechanism is designed to execute spiral maneuvers while maintaining contact with the pipeline surface during rotation. The in-pipe inspection robot is configured with wireless communication modules and batteries, allowing for wireless operation. Following its development, the inspection robot underwent driving experiments in actual pipelines to validate its performance. The field test bed used for these experiments is approximately 1 km in length. Results from the driving experiments on the field test bed confirmed the robot's ability to navigate various curvatures and obstacles within the pipeline. It is posited that the use of the developed in-pipe inspection robot can reduce economic costs and enhance the safety of inspectors when examining aging pipes. [ABSTRACT FROM AUTHOR]

To generate stable walking of a quadruped, the complexity of the configuration of the robot involves a significant amount of optimization that decreases to its time efficiency. To address this issue, a machine learning method was used to build a simplified control policy using joint models for the supervised training of quadruped robots. This study considered 12 joints for a four-legged robot, and each joint value was determined based on the conventional method of walking simulation and prepossessed, equaling 2508 sets of data. For data training, the multilayer perceptron model was used, and the optimized number of epochs used to train the model was 5000. The trained models were implemented in robot walking simulations, and they improved performance with an average distance error of 0.0719 m and a computational time as low as 91.98 s. [ABSTRACT FROM AUTHOR]

The present study describes the development of a wearable device designed to assist those who work in an unstructured posture. In the manufacturing sector, industrial accidents have been steadily on the rise due to poor work environments and excessive workloads imposed on workers. Against this backdrop, the present study aimed to analyze various types of work, especially those performed in unstructured postures by heavy industry workers, who are frequently exposed to high workloads and poor work environments. Based on the analysis results, an attempt was made to develop a shoulder muscle-assistive wearable device capable of assisting a wearer who is working using their shoulder muscles. Various types of unstructured posture work are performed in heavy industries, including activities such as the welding and grinding of ship components and plant structures. They are typically conducted in narrow spaces with limited postures, causing many workers to suffer muscle fatigue. In the present study, as the first step of developing a shoulder muscle-assistive wearable device, different working scenarios were simulated, and the corresponding motion data and required torque values were estimated using motion capture devices. The obtained motion data and required torque values were reflected in the design of the wearable device. The main structural body of the shoulder muscle-assistive wearable device was made of a carbon fiber-reinforced composite to be lightweight. This shoulder muscle-assistive wearable device was designed to fully cover the range of motion for workers working in unstructured postures while generating the torque required for a given job, thereby enhancing the muscular endurance of the workers. The gravity compensation module of the designed shoulder muscle-assistive wearable device generates a support force of 4.47 Nm per shoulder. The shoulder muscle assistive wearable device was developed to provide support for approximately 30% of the shoulder joint's maximum torque generated in overhead tasks. This shoulder muscle-assistive wearable device is expected to contribute to improving the productivity of field workers, while reducing the occurrence of musculoskeletal injuries arising from the aging of the working-age population. [ABSTRACT FROM AUTHOR]

Underwater detection is accomplished using an underwater ultrasonic sensor, sound navigation and ranging (SONAR). Stealth to avoid detection by SONAR plays a major role in modern underwater warfare. In this study, we propose a smart skin that avoids detection by SONAR via controlling the signal reflected from an unmanned underwater vehicle (UUV). The smart skin is a multilayer transducer composed of an acoustic window, a double-layer receiver, and a single-layer transmitter. It separates the incident signal from the reflected signal from outside through the time-delay separation method and cancels the reflected wave from the phase-shifted transmission sound. The characteristics of the receiving and transmitting sensors were analyzed using a finite element analysis. Three types of devices were compared in the design of the sensors. Polyvinylidene fluoride (PVDF), which had little effect on the transmitted sound, was selected as the receiving sensor. A stacked piezoelectric transducer with high sensitivity compared to a cymbal transducer was used as the transmitter. The active reflection control system was modeled and verified using 2D 360° reflection experiments. The stealth effect that could be achieved by applying a smart skin to a UUV was presented through an active reflection–control omnidirectional reflection model. [ABSTRACT FROM AUTHOR]

This study presents a new combinable multi-legged modular robot that mimics the structures of ants to expand the physical capabilities of the legged robot. To do this, the robot design is focused on exploring a fusion of two robotic platforms, modular and multi-legged, in which both the body frame and the legged structure are designed to be a rectangular prism and a 3-DoF sprawling-type articulated leg structure, respectively. By imitating ants' claws, the hook-link structure of the robot as the coupling mechanism is proposed. This study includes the platform's development, and the experimental work on the locomotion in both single and combined modes is carried out. The result of this study proves that mimicking ants' structure in the proposed robots successfully enhances the capability of the conventional legged robot. It is feasible to use in a multi-robot system to realize ants' super-organized behavior. [ABSTRACT FROM AUTHOR]

This paper presents a control technique for reducing the reflection of acoustic signals for the plane array of multilayer acoustic absorbers underwater. In order to achieve this, a plane array of multilayer acoustic absorbers is proposed to attenuate low-frequency noise, with each unit consisting of a piezoelectric transducer, two layers of polyvinylidene fluorides and three layers of the acoustic window. Time-delay separation is used to find the incident and reflected acoustic signals to achieve reflected sound reduction. Experimental comparison of the attenuation rate of the reflected acoustic signal when performing passive and active controls is considered to verify the effectiveness of the time-delay separation technique applied plane array absorbers. Experiments on the plane array of smart skin absorbers confirmed that the reduction of reflected acoustic signals makes it suitable for a wide range of underwater applications. [ABSTRACT FROM AUTHOR]

Techniques for reducing the reflection of acoustic signals have recently been actively studied. Most methods for reducing acoustic signals were studied using the normal-incidence wave reduction technique. Although the technique of canceling an object from the normal incidence wave is essential, research on reducing acoustic signals according to the angle of incidence is required for practical applications. In this study, we designed, fabricated, and experimented with an active reflection controller that can reduce acoustic signals according to the angle of incidence. The controller consists of a transmitter on one layer, a receiver sensor on two layers, and an acoustic window on three layers. To reduce the reflected signal, a combination of the time delay and phase was applied to the controller to minimize the acoustic signal by up to −23 dB at an angle of 10°. A controller array simulation was performed based on the results of a controlled experiment. In conclusion, our proposed controller can reduce acoustic signals according to the angle of incidence, which makes it suitable for many applications. [ABSTRACT FROM AUTHOR]

Robotics has been used as an attractive tool in diverse educational fields. A variety of robotic platforms have contributed to teaching practical embedded programming to engineering students at universities. However, most platforms only support content with a low level of programming skills and are unlikely to support a high level of embedded programming. This low association negatively affects students, such as incomprehension, decreased participation, dissatisfaction with course quality, etc. Therefore, this paper proposed a new robotic platform with relevant curricula to improve their effectiveness. The developed platform provided practical content used in mechatronics classes and the capability to operate a robot with a high level of embedded programming. To verify the effectiveness of the proposed platform, participants (undergraduates) examined course evaluations for educational programs based on the developed platform compared with the previous year's class evaluation. The results showed that the proposed platform positively affects students' intellectual ability (performance) and satisfaction in programming education. [ABSTRACT FROM AUTHOR]

This study presents a new path planning method based on Fuzzy Analytic Hierarchy Process (FAHP) for a mobile robot to be effectively operated through a multi-objective decision making problem. Unlike typical AHP, the proposed FAHP has a difference in using triangulation fuzzy number based extent analysis to derive weight vectors among the considerations. FAHP framework for finding the optimal position in this study is defined with the highest level (goal), middle level (objectives), and the lowest level (alternatives). It analytically selects an optimal position as a sub-goal among points on the sensing boundary of the mobile robot considering the three objectives: the travel distance to the target, robot's rotation, and safety against collision between obstacles. Alternative solutions are evaluated by quantifying the relative importance for the objectives. Comparative results obtained from the artificial potential field, AHP, and FAHP simulations show that FAHP is much preferable for mobile robot's path planning than typical AHP. [ABSTRACT FROM AUTHOR]

This paper concerns the use of adaptive wave cancellation in a new multilayer smart skin sensor to attenuate the primary low-frequency noise underwater. The proposed multilayered system is designed with a piezoelectric actuator (Pb(In1/2Nb1/2)O3–Pb(Mg1/3Nb2/3)O3–PbTiO3 composite) and two layers of polyvinylidene fluoride to accelerate wave absorption. Furthermore, the use of a combination of an adaptive control scheme and a time-delay signal separation method has the potential to provide the proposed absorber system with a wave cancellation capability and thereby enable the absorber system to respond to environmental changes underwater. The use of smart piezoelectric materials and an adaptive control approach enables the absorber system to achieve the high attenuation level of the reflected waves, unlike typical absorber systems based on active noise control. Echo reduction experiments showed that the proposed piezoelectric-based multilayer sensor with an adaptive controller could attenuate reflected wave signals effectively. [ABSTRACT FROM AUTHOR]

This paper concerns the use of adaptive wave cancellation in a new multilayer smart skin sensor to attenuate the primary low-frequency noise underwater. The proposed multilayered system is designed with a piezoelectric actuator (Pb(In 1/2 Nb 1/2 )O 3 -Pb(Mg 1/3 Nb 2/3 )O 3 -PbTiO 3 composite) and two layers of polyvinylidene fluoride to accelerate wave absorption. Furthermore, the use of a combination of an adaptive control scheme and a time-delay signal separation method has the potential to provide the proposed absorber system with a wave cancellation capability and thereby enable the absorber system to respond to environmental changes underwater. The use of smart piezoelectric materials and an adaptive control approach enables the absorber system to achieve the high attenuation level of the reflected waves, unlike typical absorber systems based on active noise control. Echo reduction experiments showed that the proposed piezoelectric-based multilayer sensor with an adaptive controller could attenuate reflected wave signals effectively., Competing Interests: The authors declare no conflict of interest.