In recent years, Personal Mobility (PM), which is a small, low-speed electric vehicle, has been attracting attention as a new means of transportation to replace walking and driving, and research and development of autonomous driving technology for PM, especially to support the disabled and elderly, are underway. Since PM has a high affinity with pedestrians, it is expected to be effectively used in “shared space,” which is a road space where pedestrians, bicycles, automobiles, and streetcars coexist. In order for PM to run autonomously in the “shared space”, it is important to have a motion control method that can safely avoid obstacles of various shapes, such as pedestrians and streetcars, while considering the comfort of the occupants. Conventionally proposed methods allow PM to smoothly avoid various obstacles based on the prediction of their motion, but if the prediction deviates significantly, it becomes difficult to avoid the obstacle. Therefore, in this paper, we propose a new motion control method for PM that takes into account the motion characteristics of obstacles. Specifically, we define a new potential field that reflects the kinematic characteristics such as the magnitude and frequency of directional and velocity changes caused by obstacles, and control the motion of the PM based on this field. This is an extension of the conventional potential field method as a path planning method. Various simulation results have shown the effectiveness of the proposed method.

This paper describes an improvement of pneumatic motor response for autonomous steering of conventional six-wheel dump trucks. Pneumatic motors are robust against overload, so it is considered suitable for the steering actuator of six-wheel dump trucks from the hardware point. However, a disadvantage of the pneumatic motor is the low performance of path tracking of the vehicle because of phase delay and dead time of the motor. Therefore, to improve the problem, in this research, the following four points were implemented: (1) modeling of the plant, (2) identification of model parameters, (3) designing feedforward controller with the inverse model of the plant, (4) evaluation of responsiveness by simulation. According to the above implementations, the delay time was reduced by about 70% for the application range of the feedforward compensation. Furthermore, by clarifying the pneumatic motor's applicable condition limits, the design guideline of the path planning for dump truck according to the vehicle speed is introduced.

This study presents a fixed-time descriptor terminal sliding mode controller for the tracking control of multi-DOF (degree-of-freedom) mechanical systems. The descriptor representation is applied to the sliding surface design, which relaxes the robust stability conditions for chattering suppression. Furthermore, the proposed method attains fixed-time stability of the reaching and sliding mode. Both settling times are bounded by some fixed parameters of the controller and inertia matrix, which are independent of any initial conditions. Finally, simulations and an experiment using multi-DOF robot manipulators are conducted to validate the proposed controller.

In this paper, we address the design problem of an agri-environment control system that is constructed and operated at low costs. The key of the cost-reduction is farmers' participation in the control system: the human-in-the-loop system. In such a “human-in-the-loop” system, temperature and humidity in a greenhouse are predicted, and a prediction-based recommendation of control actions is send to the farmer. Based on the recommendation, which includes multiple options of control actions, the farmer determines his/her actions and participates to control the agri-environment in the house. The proposed prediction method and control system are verified in an experiment and a simulation, respectively.