Publikationen

This paper presents the implementation and evaluation results of the German research project SERROGA (2012 till mid 2015), which aimed at developing a robot companion for domestic health assistance for older people that helps keeping them physically and mentally fit to remain living independently in their own homes for as long as possible. The paper gives an overview of the developed companion robot, its system architecture, and essential skills, behaviors, and services required for a robotic health assistant. Moreover, it presents a new approach allowing a quantitative description and assessment of the navigation complexity of apartments to make them objectively comparable for function tests under real-life conditions. Based on this approach, the results of function tests executed in 12 apartments of project staff and seniors are described. Furthermore, the paper presents findings of a case study conducted with nine seniors (aged 68-92) in their own homes, investigating both instrumental and social-emotional functions of a robotic health assistant. The robot accompanied the seniors in their homes for up to three days assisting with tasks of their daily schedule and health care, without any supervising person being present on-site. Results revealed that the seniors appreciated the robot's health-related instrumental functions and even built emotional bonds with it.

This work introduces the IRON keypoint detector and the IRON descriptor which enable high-speed and high-accuracy alignment of 3D depth maps. Instead of using raw point values for storing 3D-scenes, all algorithms were designed to operate on Normal Distribution Transforms (NDT), since NDT-maps provide a highly memory-efficient representation of depth data. By taking into account surface curvature and object shape within NDT-maps, patches with strong surface variability can be recognized and described precisely. In this paper, the whole feature extraction process, as well as descriptor matching, outlier detection, and the final transform calculation between NDT-maps is elaborated. The presented technique is particularly insensitive to an initial offset between both maps, has a high robustness, and it achieves more than 75 NDT-map alignments per second (including complete memory allocation each time as well) in two large publicly available depth datasets while using only a single core of a modern Intel i7 CPU. Even though the main focus of this work was placed on the proposed IRON registration algorithm, two specific applications of this NDT-matching approach are outlined in the second part, namely robot pose tracking and NDT-one-shot localization within densely furnished domestic environments.