The technique of measuring temperature distribution is essential across various fields. An acoustic probe, emitting sound waves and measuring their time-of-flight (ToF) to reach a microphone, can measure the average temperature along the sound propagation path. Moreover, deploying multiple acoustic probes in the measurement space allows temperature distribution measurement with fewer sensors than conventional point-type sensors. The accuracy of temperature measurement using acoustic probes depends on precise ToF measurement. However, the impact of ToF measurement errors on temperature distribution remains thoroughly explored. Acoustic probes require a DAC/ADC with minimal input/output delay or the capacity to synchronize operations via an external trigger. This poses challenges in utilizing existing platforms like audio interfaces on single-board computers. In this study, we proposed a method to accurately measure ToF, even when random delays occur in the operation's timing. This method is achieved by transmitting loopback signal from DAC to ADC and canceling the delay between input and output. Experimental evaluations demonstrate that the proposed method exhibits an error of 0.36° C, while substracting offset of delay demonstrates an error of 0.93° C when the length of acoustic path is 2.48m. These results shows that the proposed method can eliminate the impact of audio input/output delays and precisely measure air temperature.

It is important to understand and predict the behavior of pedestrians, who are vulnerable road users, for the safe implementation of autonomous driving including on ordinary roads. Pedestrians make decisions and move considering other traffic participants, and decision-making models have been proposed to understand pedestrians' behavior. However, as the traffic situations become more complex, such as the number of vehicles, the models become more complicated and the scale of the models become larger, which makes modeling more difficult. To solve the problem, this paper models the crossing decisions of pedestrians using small-scale models by dividing the crossing decisions into decisions for each traffic participant. In the proposed model, crossing decisions of pedestrians are expressed by a Bayesian network, and the divided decisions for each traffic participant are modeled by logistic regression. Data of pedestrians' behavior were obtained using interactive multiplayer simulators, and then the proposed model was trained and validated. The accuracy of the proposed model was as good as that of the conventional model, which indicates the effectiveness of the proposed model. The proposed model succeeded in expressing crossing decisions of pedestrians in complex situations from small-scale models. Therefore, the flexibility of the model is increased in response to changes in the number of vehicles.

From the perspective of security in a living space, it is useful for a patrol robot to check and perform door closing, and this research focuses on the door closing task by a small robot. While small robot is easy to install in a living space, it has a problem that it cannot continue the task when closing a door that is large and heavy compared to its own body because of its small size. To solve this problem, the robot recognizes an open door by patrolling with an RGB-D camera and tries to hit the door without losing its posture. As a result, the door can be closed even if it is twice as heavy as it should be. The robot can also autonomously determine the path of door closing based on the presence or absence of the door closer, and performs a series of operations by removing the door stopper that serves as an obstacle with a manipulator. Finally, the system confirms whether the door is normally closed and takes appropriate action, and confirms and executes the door closing process by sequentially determining whether the door is open or closed.

We studied a gait analysis method focusing on skeleton pose estimation during gait-training using a wheeled gait-training walker. To ensure the accuracy of the gait angle parameters, we proposed a method to dynamically extract the rectangular range of an experimental participant. We also proposed to use an amplitude of the gait angle parameter by frequency-analyzed spectrum, as an evaluation. As a result, we found a correlation between left-right elbow load balance of our developed walker and left-right posture stability. This suggests that the stability can be evaluated with the walker.