In this paper, we present a water volume estimation method in various cups using the glass harp acoustics. When a rigid probe flicks a glass, sounds arise. Since the sounds alter depending on the water volume in the glass, we can utilize the sound information to estimate the water volume. In order to model the acoustics characteristics of various glasses, we propose the relational expression between the water volume and the vibration frequency that improves Oku's expression. By using the proposed relational expressions and a flicking motion by a robotic finger with a microphone, we confirm the proposed method can estimate the water volume with the accuracy of 1–3%.
This paper presents the latest results on a wearable line-of-sight (LOS) detection system using transparent optical sensors on eyeglasses. A successful LOS detection system that enables a plenty of promising applications must cause the user least stress to acquire effective information. The proposed system herein detects the position and movement of eyes by the sensors and does not require an external camera facing eyes, which alleviates both mental and physical stress on the subject. Dye sensitized photovoltaic cells were micro-fabricated and used as the transparent sensors. Fabricated photovoltaic cells were characterized and an algorithm to acquire the position and movement of the pupil was developed. The system successfully detected the center of the pupil with errors of ±3.0º and then deduced the LOS.
This paper describes a path planning and a consecutive operation based on discrete acquired motion data for an auto parking system. In order to park a car in various situations, it is necessary to plan the path that contains the turn back motion according to the situation. However, it is difficult to search the appropriate path because there are many paths to reach the target position. Therefore, the method by which combination of motions is decreased by limiting to discrete motions was proposed. Moreover, a method that generates a consecutive operation from discrete motion data was proposed. The proposed methods were applied to a model car of 1/6 scales. The results of simulations and experiments in a real environment show the effectiveness of the proposed methods.
Humanoid robots should be able to stand and walk in the presence of external disturbances. Humans usually switch the control strategies depending on disturbances: stabilization in the upright position, and falling avoidance using stepping motion. In order to achieve robustness to unknown disturbances, humanoid robots require switching the control strategies. For this purpose, it is important to explicitly consider the physical constraint in the control law. In this paper, we apply the maximal CPI set framework to the control based on the COG-ZMP inverted pendulum model. Based on the maximal CPI set, we can determine whether the constraint is broken or not. Furthermore, we improve the robustness to external disturbances by applying a switching feedback control based on the maximal CPI sets. We also present a real-time updating method of the maximal CPI set when the contact region changes. Using this updating method, a falling avoidance control method is proposed as an application. Detection of the stepping necessity based on the maximal CPI set enables the robots to switch the control strategies from the upright position stabilization to the stepping motion for falling avoidance. The validity of the proposed method is verified with simulations and experiments.
It is an important issue to make a disaster reduction plans for overcrowded population in urban cities. In this paper, we focus on evacuation guidance to prevent the damage from spreading. The personal navigation system cannot deal with evacuation guidance for the human crowd with large numbers of individuals because of time constrain and extraordinary communication error. An implicit guidance based on dynamical characteristic of swarm behavior is efficient and effective by a few guidance operators. We propose a modeling and control method of swarm based on vector field. The evacuee behavior model contains intention of evacuation, field of view, collision avoidance and evacuee group, which are represented by vector field. The guidance operator model contains indicating direction. By giving the desired vector field that indicates the safe route for evacuation, the position of guidance operators are optimally distributed. Moreover, the number of guidance operators is minimized based on the contribution index. The proposed modeling and control method is applied to the swarm robot and the effectiveness is evaluated by the experiments.