The gyroscopic power generator produces a high-speed rotation of magnets from low-frequency vibrations and supplies electric power to information and communication devices that use human vibrations in daily life. In this paper, in order to increase the stability and the output power of the generator, a simple equation that indicates the steady state approximate solution of phase difference is derived. From the derived solution, the phase difference of the precession angle is used as a margin factor of the stability. The control methods for the steady state and the transient state are then verified by the simulations. In an experiment to determine precession angle, a measurement method is developed in which the sensing coil is attached perpendicular to the generation coil and precession angle is obtained from the envelope of the coil voltage. In order to maintain the stability and high power generation for variable input vibrations, the impedance control method using the phase difference is developed and verified experimentally.
A poly vinyl chloride (PVC) gel actuator shows great potential because of such positive characteristics as movement in the air, large deformation, and being lightweight. We have developed a contraction type actuator –. In this study, we propose an application of the PVC gel actuator to negative actuated brakes. We made an experimental apparatus which consisted of a motor with an encoder, a torque sensor and a brake using the PVC gel actuator. We measured the characteristics of the polymer brake by using the experimental apparatus. The followings are the results that we found from the experiments. The static brake torque is more than 70[mNm], and the response rate is about 0.04[s]. Based on the results, we showed that the proposed brake was useful for small motors.
This paper describes analysis of the 1–Joint Spring–Motor Coupling System (SMCS). A system which includes series elastic elements shows vibrational responses in the velocity space, and our concept is to use the velocity peak of the system for dynamic motions such as pitching motions. By tuning parameters, we can obtain momentarily higher velocity than a system without any spring. We constructed a mathematical model of the 1–Joint SMCS and confirmed the velocity increasing effect by numerical analyses and real experiments. We also derived existence of the most effective inertia balance and the optimum spring constant. We established design criteria to utilize the effect and confirmed the criteria by experiments.
This paper presents a proximity sensor for recognizing an object in 360º all around with response time only 1[ms]. The sensor applies unique design of analog net-structure circuit, which enables all-face mounting on various peripheries, fast-response, and simplification of information processing. Thus, the sensor is especially available for avoiding sudden contact with rapidly approaching objects for mobile robots, robot arms, robot hands, and other robotic systems. In this paper, the structure and detecting principle of the sensor are firstly described, then, its detection property is tested by experiments. The result shows that the sensor recognizes the angle of the nearby object with accuracy of 3[deg]. Furthermore, as practical use of the sensor, a large size model is produced for a mobile robot to achieve omni-directional sensing. By using the application model, two detection methods are discussed on situations where the number or the position of objects differs.
We develop a composite sensor for capturing color range images that are used for recognizing and modeling the 3D shape of unknown objects. To achieve fast modeling of these objects, we propose a novel method of matching 3D point cloud templates using color histograms. Given raw 3D measurements coming from this sensor, our algorithm can discover and model new objects like chairs and tables, which is vital for navigation among movable obstacles. Furthermore, we utilize this method for computing a dynamic map of the environment by estimating the 6D pose of the sensor at every sample. We show experimental results on the HRP-2 humanoid robot walking around the environment while dynamically building a map and segmenting out movable objects.
This paper describes method to improve the accuracy of localization of mobile robot using GPS with particle filter. This method improves the accuracy of localization by removing multipath of GPS measurement data with 3D-Map. This approach analyzes area that cannot receive direct wave from GPS satellite with 3D-Map about each satellite. The particles in that area are assumed to be receiving GPS data including the multipath error. And particle's likelihood is calculated considering the multipath error. This method is useful for localization and navigation of mobile robot between buildings.
In this paper, we propose an omni-directional mechanism for a wheeled inverted pendulum type mobile platform. The omni-directional mechanism consists of three omni-directional wheels located at the bottom of the mobile platform. The two wheels are located at the left and right side of the platform as a conventional two-wheeled mobile platform, and other one is located between the two wheels, which has an axis perpendicular to those of two wheels. The grounding points of all wheels are on the same line in order to realize balancing control. A simple driving experiment was conducted to examine the driving performance, and it was confirmed that the proposed mobile platform could realize an omni-directional motion while maintaing its balance.
We present a reactive method for online robot motion replanning in dynamically changing environments by combining path replanning and deformation. Path deformation is integrated in a replanning method featured by parallel planning and execution. The proposed reactive planner can handle dynamic environments including continuously moving obstacles by smoothly deforming the path during execution. If the collisions cannot be removed by path deformation, alternative paths can be replanned efficiently by using continuously updated roadmaps. Simulation results are shown to validate the effectiveness of the proposed method.
In order for multiple mobile robots to solve congestion, a novel methodology that consists of two approaches, intelligent cruise control technique and behavior rule, is proposed in this paper. For this purpose, first, our previously-proposed cruise control technique is improved. This enables robots to reduce velocity not only for the congestion preceding them, but also for the decelerating robot in front, using external interaction force generated among robots with a virtual damper. After that, a behavior rule in connection with the intelligent cruise control technique is designed and provided on congested lanes where robots slowly move. Thus, stronger interaction force affects the robots, and they move more slowly on the congested lanes. In simulation experiments, the proposed methodology is compared to two other cruise control techniques. These are quantitatively evaluated on the basis of a criterion, i.e., behavioral feature, such as average velocity of all the robots and standard deviation of each velocity. Finally, the effectiveness of the methodology for solving the congestion is shown.
In the densely-populated urban cities, pedestrian flows often cross each other and congestion occurs. Due to the congestion, we feel discomfort and accidents may occur. In order to reduce the congestion or the risk of accidents, it is required to control swarm behavior of pedestrian flows so that the flows become smooth. This paper proposes the control method of the crossing pedestrian flows. First, we propose the continuum model of the crossing flows. In the actual pedestrian flows, it is known that people formulate the diagonal stripe pattern in the crossing area. The continuum model enables us to quantify such dynamical change of the congestion degree. Then, we propose an implicit control method of the crossing flows. Utilizing the dynamical characteristics of the flows, swarm behavior is controlled by moving a few guides without explicit guidance. From analysis on the crossing flows, we derive a control algorithm to improve the average flow velocity. The proposed control method is also applied to the particle model, assuming the actual pedestrian flows. The validity is verified with simulations in both the continuum and particle models.
This paper describes an approach to structuring behavioral knowledge based on symbolization of human whole body motions, hierarchical classification of the motions, and extraction of the causality among the motions. The motion patterns are symbolized by Hidden Markov Models (HMMs), which can be used for recognition of the motion patterns. The HMMs are called “motion symbol” since they abstract their corresponding motion patterns. The motion patterns are organized into a hierarchical tree structure (“motion symbol tree”) representing the property of spatial similarity among the motion patterns. The motion patterns are classified based on the motion symbol tree. The sequences of the motion patterns are stochastically represented as transitions between the abstracted motion patterns by using an N-gram model (“motion symbol graph”), and the temporal causality among the human behaviors are extracted. The integration of the motion symbol tree and the motion symbol graph makes it possible to recognize motion patterns fast and predict human behavior during observation as if the behaviors in the future are reflected in a Crystal Ball. The experiments on a large motion dataset validate the proposed framework.