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The majority of studies on mastication movements have focused on chewing movements. In recent years, however, it has come to be thought that tongue action also plays a very important role in masticatory movements.

This paper focuses on a dynamic behaviour of mass measurement system to achieve dynamic measurement of the mass of a target object. To improve an accuracy of mass measurement, we have investigated an effect of a fulcrum point position shift via simulation. In this paper, we design a new experimental system that can evaluate the effect of the fulcrum point position shift. Also, we propose a new model of our mass measurement system with consideration of the fulcrum point position shift. To evaluate a validity of the proposed model of our mass measurement system, we compare experimental results with simulation results. After that we discuss an effectiveness of our proposed mathematical model of our mass measurement system.

We propose a framework for evasive maneuver assist using an array of high-speed cameras capable of communicating with each other via a network, called networked high-speed vision. The system has a wide field-of-view and high responsiveness, enabling vehicles to receive information about potential dangers immediately after it appears around them, thus allowing them to perform evasive maneuvering as quickly as possible. We demonstrated the effectiveness of the proposed system in a typical scenario in which evasive maneuvering is performed. Experiments with a robotic car platform and simulations showed that the proposed system outperformed a system composed of a video-rate camera.

This research aims to realize robotic planar-contour tracing of unknown object with high-speed and high accuracy. The challenge lies in the existence of uncertainties, which can be attributed to a robot itself (such as modeling errors, mechanical defects like backlash) or due to environmental issues (like calibration errors, pose fluctuation of a workpiece). We propose to realize the tracing task by a non-model-based dynamic compensation approach based on the coarse-to-fine philosophy, which enables the manipulation with high speed and good accuracy simultaneously. This is achieved by adopting a methodology where a main robot is performing fast but coarse motion, while an add-on module is conducting accurate compensation of the overall uncertainties using high-speed visual feedback as well as force-torque feedback. Experiments for verifying the proposed method are conducted.

This study explored the association of 14 single nucleotide polymorphisms in three genes coding for influx transporters (SLC22A1, SLCO1B1, and SLCO1B3), two genes coding for efflux transporters (ABCB1and ABCG2), and four genes coding for enzymes (CYP2C9, CYP2C19, CYP2D6, and CYP3A5) with the pharmacokinetics of imatinib in Japanese patients with chronic myeloid leukemia. Pharmacokinetic parameters were estimated by a population pharmacokinetic analysis based on 622 plasma samples from 34 patients at steady state. Approximately 4.6-fold variability in individual clearance was observed (range, 3.4-15.5 L/hr). The individual estimated clearance was significantly increased in patients with the SLCO1B3334GG genotype (median value ± standard deviation, 9.5 ± 3.1 L/hr; n = 19) compared with SLCO1B3334TT and TG genotypes (7.0 ± 3.1 L/hr; n = 15) (P= 0.019). Patients with the ABCB13435CC genotype had significantly higher imatinib clearance (12.7 ± 3.0 L/hr; n = 7) compared with patients with ABCB13435CT and TT genotypes (7.9 ± 2.7 L/hr; n = 27) (P= 0.035). In conclusion, the present study suggests that single nucleotide polymorphisms of the influx transporter SLCO1B3and the efflux transporter ABCB1were functionally associated with individual variability of imatinib pharmacokinetics in Japanese patients with chronic myeloid leukemia.

In this paper, we propose an entirely new strategy for dynamic manipulation of sheet-like flexible objects. As one example, we consider dynamic folding of a cloth by a high-speed robot system consisting of two high-speed multifingered hands mounted on two sliders and a high-speed vision system. First, the dynamic folding performed by a human subject is analyzed in order to extract the necessary motion for this task. Second, a model of a sheet-like flexible object is proposed by extending a linear flexible object model (algebraic equation) using high-speed motion. Third, motion planning of the robot system is performed by using the proposed model, and the simulation result of the dynamic folding is shown. Fourth, high-speed visual feedback control is proposed in order to enhance the manipulation strategy. Finally, experimental results of the dynamic folding of the cloth by the high-speed robot system are shown.

This paper focuses on behavior of a dynamic mass measurement system. The goal of this paper is to propose a dynamic model of the system, which can reproduce dynamic behavior to floor vibration. The dynamics of our system with electro-magnetic force compensation is approximated by a mass-spring-damper system, and an equation of motion is derived. Model parameters are also estimated from experimental data. Then, comparisons of the simulation results with the realistic responses are carried out. Finally, we explore the dynamic behavior to floor vibration.

We propose an acceleration method for correlation-based object tracking. Correlation-based tracking methods involve an inverse Fourier transform, which is a bottleneck in acceleration. We exploit a trait of high-speed vision to accelerate this computation: namely, we assume that displacements between consecutive frames do not change dramatically within a short frame acquisition interval. By limiting a small region where the displacement is assumed to be, we propose to reduce computational cost in the inverse Fourier transform. We implemented the proposed method in phase-only correlation and conducted experiments using both simulated and real data. We achieved a computation speed around five-times faster than the conventional method without sacrificing accuracy. The proposed method provides as a useful building block in accelerating correlation-based object tracking.

In this study we successfully demonstrated a dexterous manipulation of sheet-like elastic objects — namely playing cards — using a high-speed multifingered robot hand system. Our goal in this research was to achieve card flicking by vibrating a fingertip of the robot hand at high speed. Firstly, we discuss card grasping in the initial state based on the geometrical conditions of the card and the kinematics of the robot hand. Secondly, we propose a strategy for performing the card flicking. In addition, we obtain the card-flicking conditions by analysing the slip between the card and the fingertip of the robot hand. In addition, we analyse an energy transition of the card based on the physical law. Thirdly, we estimate a spring constant of the card via a vibrational experiment. Then we simulate the trajectory of a flying card after the slippage, and compare a simulation result with an experimental result of the flying card's trajectory. Finally, we show the experimental results of card flicking using the high-speed robot system and the proposed method.

This paper deals with the issue of non-model-based position regulation for the dynamic compensation robotic system (DCRS), which has been proposed for cooperating with the existing main robotic systems, such as the common serial robotic arms, to accomplish high-speed and accurate manipulations. The dynamic compensation concept is realized by fusing a high-speed & light-weight compensation actuator as well as endpoint closed loop (ECL) configured high-speed cameras. Within the context of the DCRS, the coarse motion, which is realized by the main robotic system, usually gives rise to negative dynamic impact on the compensation actuator that is configured to accomplish the fine motion. Through the analysis of a simplified model for the coupled two-plant system, relative velocity information between the two plants is found to play a role in the first order derivative of the displacement error. With the use of the relative position information from high-speed visual feedback, this paper proposes a new pre-compensation fuzzy logic control (PFLC) approach for control of the compensation actuator. The PFLC method is model-independent and is realized with a cascade fuzzy inference structure that conveniently integrates the relative velocity term between the two plants into the error regulation, and therefore realizes the partial counteraction of the disturbance from the main robot easily without knowing the explicit mathematical models of the system. Comparison works between the proposed PFLC and approaches that take no consideration of the relative velocity information, such as proportional-derivative (PD) control and conventional fuzzy logic control, are conducted. Simulations and experiments show the consistent effectiveness of the proposed approach.

In this paper we suggest an entirely new strategy for the dexterous manipulation of a linear flexible object, such as rope or a cable, with a high-speed manipulator. We deal with a flexible rope as one example of the linear flexible object. The strategy involves manipulating the object at high-speed. By moving the robot at high-speed, we can assume that the dynamic behaviour of the flexible rope can be obtained by performing algebraic calculations of the high-speed robot motion. Based on this assumption, we derive a dynamic deformation model of the flexible rope and confirm the validity of the proposed model. Then we perform a simulation of dynamic, high-speed knotting based on the proposed model. We also discuss the possibility of forming the knot based on a simple analysis model. Finally, we show experimental results demonstrating dynamic, high-speed knotting with a high-speed manipulator.