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This study proposes an autonomous lane-changing system for congested merging areas. Manual and autonomous vehicles are expected to coexist until all vehicles are substituted by autonomous vehicles. Therefore, interactions between humans and autonomous driving systems should be discussed. This study assumed a scenario in which an autonomous vehicle performed a lane change to a congested main lane, where all vehicles were manual. The proposed system estimated the possibility of changing lanes without collisions. A driving simulator was used to measure the lane-changing operations of human drivers in a congested merging area, and the proposed method was developed based on the experimental results. Simulations demonstrated that the proposed method could safely change lanes. [ABSTRACT FROM AUTHOR]

A prototype system based on a combination of 4π sensitive gamma imaging and simultaneous localization and mapping (SLAM) was developed to find unknown radiation source(s) rapidly. The system consisted of a spherical visible camera, a three-dimensional light detection and ranging, a CdTe pixel array detector for 4π gamma imaging, a portable battery, and a control laptop personal computer; these were mounted on an unmanned vehicle. In a search area of 16 × 16 m2 with a height of 3 m, the prototype system successfully demonstrated the finding of a 137Cs point source with an activity of 0.67 MBq in the surrounding thin walls. [ABSTRACT FROM AUTHOR]

Mobile robots operating in public environments require the ability to navigate among humans and obstacles in a socially compliant and safe manner. Previous work has shown the power of deep reinforcement learning (DRL) techniques by employing them to train efficient policies for robot navigation. However, most DRL-based robot navigation methods only consider dynamic pedestrians and do not take static obstacles into account. The ability to approach pedestrians and obstacles differently will improve a robot's navigation efficiency. In this work, we propose a novel network, the obstacle-robot uni-action (ORU) network, to encode the one-way direct effects of obstacles on the robot. Obstacles' indirect effects on the robot, represented by the obstacle-human uni-action (OHU), together with human–human interaction (HHI), are concatenated to a human–robot interaction (HRI) network to obtain the features of a crowd's effects on the robot. We also implement a variable reaching goal reward and an approaching goal reward in our model, which can enhance the method's performance in terms of navigation time. Results of test experiments in both simulation and real datasets demonstrate that the proposed method outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper presents an estimation method for a sound source of pre-recorded mallard calls from acoustic information using two microphone arrays combined with delay-and-sum beamforming. Rice farming using mallards saves labor because mallards work instead of farmers. Nevertheless, the number of mallards declines when they are preyed upon by natural enemies such as crows, kites, and weasels. We consider that efficient management can be achieved by locating and identifying the locations of mallards and their natural enemies using acoustic information that can be widely sensed in a paddy field. For this study, we developed a prototype system that comprises two sets of microphone arrays. We used 64 microphones in all installed on our originally designed and assembled sensor mounts. We obtained three acoustic datasets in an outdoor environment for our benchmark evaluation. The experimentally obtained results demonstrated that the proposed system provides adequate accuracy for application to rice–duck farming. [ABSTRACT FROM AUTHOR]

In this study, a new method of estimating the leakage positions of cooling water using a stereo camera for the Fukushima Daiichi Nuclear Power Plant (FDNPP) is proposed. A stereo camera mounted on an inspection system with a rotating base was inserted into the pedestal below the reactor pressure vessel (RPV), and the waterdrops from the leakage position were captured using a stereo camera. We estimated the leakage positions by triangulating the waterdrop trajectory lines in the stereo image. The main contribution of this study is the extraction and matching of the waterdrop trajectories in a stereo image in the FDNPP. The radiation noise is intense inside the pedestal because of the presence of fuel debris. Therefore, we propose a method that is robust against radiation noise. We assume that the waterdrops drip vertically in indoor environments without wind, such as in the FDNPP. Hence, the orientation of the stereo camera can be adjusted by the rotating base such that the vertical lines in the three-dimensional space are also projected as vertical lines in the image planes. Thereafter, the columns of pixels in the images are treated as image features and used to extract and match the waterdrop trajectories. We demonstrated the effectiveness of our leakage position estimation method in a simulated environment of the FDNPP with gamma-ray image noise. [ABSTRACT FROM AUTHOR]