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.