It is important to measure and analyze people behavior to design systems which interact with people. This article describes a portable people behavior measurement system using a three-dimensional LIDAR. In this system, an observer carries the system equipped with a three-dimensional Light Detection and Ranging (LIDAR) and follows persons to be measured while keeping them in the sensor view. The system estimates the sensor pose in a three-dimensional environmental map and tracks the target persons. It enables long-term and wide-area people behavior measurements which are hard for existing people tracking systems. As a field test, we recorded the behavior of professional caregivers attending elderly persons with dementia in a hospital. The preliminary analysis of the behavior reveals how the caregivers decide the attending position while checking the surrounding people and environment. Based on the analysis result, empirical rules to design the behavior of attendant robots are proposed.

No abstract

BackgroundHost-associated microbiota is often acquired by horizontal transmission of microbes present in the environment. It is hypothesized that differences in the environmental pool of colonizers can influence microbiota community assembly on the host and as such affect holobiont composition and host fitness. To investigate this hypothesis, the host-associated microbiota of the invertebrate eco(toxico)logical model Daphnia was experimentally disturbed using different concentrations of the antibiotic oxytetracycline. The community assembly and host-microbiota interactions when Daphnia were colonized by the disturbed microbiota were investigated by inoculating germ-free individuals with the microbiota.ResultsAntibiotic-induced disturbance of the microbiota had a strong effect on the subsequent colonization of Daphnia by affecting ecological interactions between members of the microbiota. This resulted in differences in community assembly which, in turn, affected Daphnia growth.ConclusionsThese results show that the composition of the pool of colonizing microbiota can be an important structuring factor of the microbiota assembly on Daphnia, affecting holobiont composition and host growth. These findings contribute to a better understanding of how the microbial environment can shape the holobiont composition and affect host-microbiota interactions.

Pedestrian detection is one of the key technologies for autonomous driving systems and driving assistance systems. To predict the possibility of a future collision, these systems have to accurately recognize pedestrians as far away as possible. Moreover, the function to detect not only people walking but also people who are standing near the road is also required. This paper proposes a method for recognizing pedestrians by using a high-definition LIDAR (light detection and ranging). Two novel features are introduced to improve the classification performance. One is the slice feature, which represents the profile of a human body by widths at the different height levels. The other is the distribution of the reflection intensities of points measured on the target. This feature can contribute to the pedestrian identification because each substance has its own unique reflection characteristics in the near-infrared region of the laser beam. Our approach applies a support vector machine (SVM) to train a classifier from these features. The classifier identifies the clusters of the laser range data that are the pedestrian candidates, generated by pre-processing. A quantitative evaluation in a road environment confirms the effectiveness of the proposed method.

No abstract