Kazushi Sanada

We propose a data-driven approach for modelling an organism's behaviour instead of conventional model-based strategies in chemical plume tracing (CPT). CPT models based on this approach show promise in faithfully reproducing organisms’ CPT behaviour. To construct the data-driven CPT model, a training dataset of the odour stimuli input toward the organism is needed, along with an output of the organism’s CPT behaviour. To this end, we constructed a measurement system comprising an array of alcohol sensors for the measurement of the input and a camera for tracking the output in a real scenario. Then, we determined a transfer function describing the input–output relationship as a stochastic process by applying Gaussian process regression, and established the data-driven CPT model based on measurements of the organism’s CPT behaviour. Through CPT experiments in simulations and a real environment, we evaluated the performance of the data-driven CPT model and compared its success rate with those obtained from conventional model-based strategies. As a result, the proposed data-driven CPT model demonstrated a better success rate than those obtained from conventional model-based strategies. Moreover, we considered that the data-driven CPT model could reflect the aspect of an organism’s adaptability that modulated its behaviour with respect to the surrounding environment. However, these useful results came from the CPT experiments conducted in simple settings of simulations and a real environment. If making the condition of the CPT experiments more complex, we confirmed that the data-driven CPT model would be less effective for locating an odour source. In this way, this paper not only poses major contributions toward the development of a novel framework based on a data-driven approach for modelling an organism’s CPT behaviour, but also displays a research limitation of a data-driven approach at this stage.

A laminar flowmeter that estimates the unsteady flowrate in a pipe using a Kalman filter is proposed. The laminar flowmeter has 32 narrow pipes. Kalman filtering is applied to one of the narrow pipes to estimate its flowrate. Three pressure sensors are connected to the narrow pipe. Upstream and downstream pressure signals are applied to a model of pipeline dynamics. The midpoint pressure is calculated and compared with the measured value. The error signal is fed back to the model. According to the principle of the Kalman filter, the estimated flowrate converges to the real flowrate. The Kalman-filtering estimation is conducted in a real-time computing system. In this study, the steady flowrate in a pipe is estimated and calibrated with measured data. The proposed Kalman-filtering-based laminar flowmeter demonstrates very promising performance.

Automatic mechanical transmission (AMT) with a gearshift assistant mechanism is a novel transmission architect concept aiming to improve the torque interruption and driveline jerk of AMT. During the shifting process, the shifting performance deteriorates as the varying road gradient and the friction coefficient worsen the coupling effect between the motor torque and the clutch friction torque. This paper focuses on improving the controller’s robustness of AMT with a gearshift assistant mechanism against the perturbed parameters during the stage of torque gap filling. In this paper, a detailed powertrain simulation model was presented. Based on a decoupling controller and a disturbance compensator, proportional-integral-differential (PID) controllers are applied to enhance the robustness and the decoupling effect. The PID parameters are automatically tuned by employing the Nelder-Mead method. In the tuning process, a cost function was established to demonstrate the outputs’ reference tracking performance, and the PID parameters are tuned by minimizing the cost function. Finally, the tuned parameters are stored in PID maps to make them adjustable online. Simulation results show that with the perturbed parameters well estimated, the upshift process was successful and the torque filling effect was also acceptable. The proposed transmission is a promising structure for industry applications.

In this paper, we proposed a sampling mechanism with flicking motion for chemical plume tracing (CPT). CPT stands for a task to locate a chemical source according to the chemical in the air. Capability of CPT by an autonomous robot is highly demanded because that can be applicable for rescue surveys, security inspections, and resource searching, yet that was difficult for an individual robot due to the complex behavior of airflow. From the viewpoint of bio-inspired systems, we focused on the flicking of an insect, by which it swings its antennae (chemical sensors) depending on situations. We expected the flicking provided variable sampling resolutions according to searching phases. We first design and implemented a variable air sampling mechanism that gave flicking ability to an autonomous mobile robot. Then, we introduced the flicking to a common CPT algorithm inspired by the programmed behavior of a silkworm moth, which was composed of three action phases. For the action phases, we tested the all combinations of wide or narrow range of the sampling system. We verified CPT performance with the proposed device through experiments. The results indicated that the flicking could improve success ratio of CPT tasks without extending needed time for a search.

In this study, we investigated the relationship between the performance of chemical plume tracing (CPT) and odor sensing property. Tracking of chemical plumes plays an important role because it facilitates the identification of an odor source. Conventional research has focused on the development of CPT algorithms, whereas the influence of the performance odor sensors on CPT performance has not been investigated. Therefore, in this study, we first compared the olfactory characteristics of an insect (silkworm moth, Bombyx mori), which has high CPT performance and the characteristics of an artificial odor sensor. In particular, we focused on and compared the recovery time of the two types of sensors, which plays an important role in the acquisition of odor information. As a result, it was determined that the recovery time for the insect olfactory sensor was 10 times faster than that of the artificial odor sensor. We also experimentally evaluated the effect of this difference in the recovery time on CPT performance. CPT experiments using silkworm moths and a robot revealed that there was a correlation between the CPT performance and sensor recovery time. As such, it was demonstrated that it is necessary to improve not only the algorithm but also the sensor recovery time improve the CPT performance.

Accumulator is an important component for oil-hydraulic circuits. It is used for storing energy, absorbing pulsation flow, and suppressing surge pressure. For predicting accumulator performance, mathematical models of the accumulator have been investigated by many researchers. In the mathematical models of accumulator, an equation of state of gas, thermodynamics, and heat transfer have been considered. The aim of this paper is to propose a mathematical model of bladder-type accumulator considering heat conduction effect inside rubber membrane. Experiments were carried out using a bladder-type accumulator which was connected to a piston-type accumulator. The bladder-type accumulator was prefilled first and then discharged, the piston-type accumulator was charged by the oil discharged from the bladder-type accumulator. Discharging process of the bladder-type accumulator and charging process of the piston-type accumulator were measured simultaneously. The accumulator model proposed was validated by measured date of the experiments.