As robots become increasingly integrated into human society, the importance of human–machine interfaces continues to grow. This study proposes a faster and more accurate control system for myoelectric prostheses by considering the Electromechanical Delay (EMD), a key characteristic of Electromyography (EMG) signals. Previous studies have focused on systems designed for wrist movements without attempting implementation. To overcome this, we expanded the system’s capability to handle more complex movements, such as those of fingers, by replacing the existing four-channel wired EMG sensor with an eight-channel wireless EMG sensor. This replacement improved the number of channels and user convenience. Additionally, we analyzed the communication delay introduced by this change and validated the feasibility of utilizing EMD. Furthermore, to address the limitations of the SISO-NARX model, we proposed a MISO-NARX model. To resolve issues related to model complexity and reduced accuracy due to the increased number of EMG channels, we introduced ridge regression, improving the system identification accuracy. Finally, we applied the ZPETC+PID controller to an actual servo motor and verified its performance. The results showed that the system reached the target value approximately 0.240 s faster than the response time of 0.428 s without the controller. This study significantly enhances the responsiveness and accuracy of myoelectric prostheses and is expected to contribute to the development of practical devices in the future.

This paper presents an approach to the estimation of a window shape for increasing the adaptability of glass façade-cleaning robots to different buildings. For this approach, a window scanning robot equipped with a 2D laser range scanner installed perpendicularly to a window surface is developed for the testbed, and a method for the window shape estimation is proposed, which consists of the robot’s pose estimation with an extended Kalman filter (EKF) and the loop closure based on the robot’s pose estimated. The effectiveness of the proposed approach is demonstrated through an experiment that is carried out on a window placed on a floor. The experimental results show that the window scanning robot can acquire a window shape, moving on a window surface, and the proposed approach is effective in increasing the accuracy of the window shape estimation.

A transformable wheel designed in this study is proposed to meet the increasingly complex travel requirements of people because it is urgent to provide a smooth and barrier-free travel scheme in complex and changeable urban land. The transformable wheel, with 10 pivoting-head parts, allows vehicles with the wheels to surmount low-height obstacles that deliberately complicates the terrain such as blind roads, small steps, bumps and door sills, and to achieve low-consumption travel. In this study, we demonstrate that the transformable wheels improve its performance by nearly 30% under the road conditions of low-height obstacles and is especially suitable for carts and suitcases passing through low-height obstacles such as blind lanes and low stairs.

The purpose of this study is to realize a power steering control that restores the maneuverability of the bicycle by assisting in handlebar operation during loading according to the analysis of the effect of loading children and luggage in the front basket on maneuverability. Placing baggage and child in the front basket of a bicycle causes an increase in the moment of inertia around the handlebar axis and a change in the position of the center of gravity, and leads to a decrease in the maneuverability of the bicycle. To solve the issue, previous studies have contributed to improve the maneuverability by applying the assist torque proportional to the user’s steering one by a power steering mechanism. However, in general, bicycle steering is affected not only by handlebar operation but also by the roll angle of the bicycle body through the trail effect. Therefore, in this study, we propose to design a control system to realize the variable trail effect, which is related to the roll angle of the bicycle body, and use it as the steering assist. To verify the effectiveness of the proposed method, we developed a bicycle equipped with the power steering mechanism and implemented the proposed control algorithm. The behavior of the experimental bicycle during straight-line and slalom biking has been analyzed, and it has been shown that the control system with the variable trail effect can recover maneuverability when a weight is placed in the front basket.

This study addresses the ’last-mile’ transportation challenges that arise in steep and narrow forest terrain by proposing a novel robotic palanquin system called roCaGo. It is inspired by the mechanical principles of two-wheel-steering and two-wheel-drive (2WS/2WD) bicycles. The roCaGo system integrates front- and rear-wheel-drive mechanisms, as well as a central suspension structure for carrying loads. Unlike conventional forestry machinery, which requires wide, well-maintained roads or permanent rail systems, the roCaGo system enables flexible, operator-assisted transport along narrow, unprepared mountain paths. A dynamic model of the system was developed to design a stabilization control strategy, enabling roCaGo to maintain transport stability and assist the operator during navigation. Numerical simulations and preliminary physical experiments demonstrate its effectiveness in challenging forest environments. Furthermore, the applicability of roCaGo has been extended to include use as a mobile third-person viewpoint platform to support the remote operation of existing forestry equipment; specifically the LV800crawler vehicle equipped with a front-mounted mulcher. Field tests involving LiDAR sensors mounted on roCaGo were conducted to verify its ability to capture the environmental data necessary for non-line-of-sight teleoperation. The results show that roCaGo is a promising solution for improving labor efficiency and ensuring operator safety in forest logistics and remote-controlled forestry operations.