Erik Einhorn

TOOMAS: Interactive Shopping Guide robots in everyday use - final implementation and experiences from long-term field trials

The paper gives a comprehensive overview of our Shopping Guide project, which aims at the development of interactive mobile shopping companion robots for everyday use in challenging operating environments such as home improvement stores. It is spanning an arc from the expectations and requirements of store owners and customers, via the challenges of the shopping scenario and the operating environment, the implemented functionality of the shopping guide robots, up to the results of long-term field trials. The field trials started in April 2008 and still ongoing aim at studying whether and how a group of interactive mobile shopping guide robots can operate completely autonomously in such everyday environments and how they are accepted by uninstructed customers. In these field trials, where nine robotic shopping guides traveled together 2187 kilometers in three different home improvement stores in Germany, more than 8,600 customers were successfully guided to the locations of their products of choice. With the successful development of these shopping guide robots, a further important step towards assistive robotics for daily use has been done.

Progress in developing a socially assistive mobile home robot companion for the elderly with mild cognitive impairment

The paper is addressing several aspects of our work as part of the European FP7 project “CompanionAble” and gives an overview of the progress in developing a socially assistive home robot companion for elderly people with mild cognitive impairment (MCI) living alone at home. The spectrum of required assistive functionalities and services that have been specified by the different end-user target groups of such a robot companion (the elderly, relatives, caregivers) is manifold. It reaches from situation-specific, intelligent reminding (e.g. taking medication or drinking) and cognitive stimulation, via mobile videophony with relatives or caregivers, up to the autonomous detection of dangerous situations, like falls, and their evaluation by authorized persons via mobile telepresence. From the beginning, our approach has been focused on long-term and everyday suitability and low-cost producibility as important prerequisites for the marketability of the robot companion. Against this background, the paper presents the main system requirements derived from user studies, the consequences for the hardware design and functionality of the robot companion, its system architecture, a key technology for HRI in home environments - the autonomous user tracking and searching, up to the results of already conducted and ongoing functionality tests and upcoming user studies.

Realization and user evaluation of a companion robot for people with mild cognitive impairments

This paper presents results of user evaluations with a socially assistive robot companion for older people suffering from mild cognitive impairment (MCI) and living (alone) at home. Within the European FP7 project “CompanionAble” (2008-2012) [1], we developed assistive technologies combining a mobile robot and smart environment with the aim to support these people and assist them living in their familiar home environment. For a final evaluation, user experience studies were conducted with volunteer users who were invited to a test home where they lived and freely used the robot and integrated system over a period of two days. Services provided by the companion robot include reminders of appointments (pre-defined or added by the users themselves or their informal carer) as well as frequent recommendations to specific activities, which were listed e.g. by their family carers. Furthermore, video contact with relatives and friends, a cognitive stimulation game designed especially to counter the progress of cognitive impairments, and the possibility to store personal items with the robot are offered. Recognition of the user entering or leaving the home is triggering situation specific reminders like agenda items due during the (expected) absence, missed calls or items not to be forgotten. Continuing our previous work published in [2], this paper presents detailed description of the implemented assistive functions and results of user studies conducted during April and May 2012 in the smart house of the Dutch project partner Smart Homes in Eindhoven, The Netherlands.

MIRA - middleware for robotic applications

In this paper, we present MIRA, a new middleware for robotic applications. It is designed for use in real-world applications and for research and teaching. In comparison to many other existing middlewares, MIRA employs novel techniques for communication that are described in this paper. Moreover, we present benchmarks that analyze the performance of the most commonly used middlewares ROS, Yarp, LCM, Player, Urbi, and MOOS. Using these benchmarks, we can show that MIRA outperforms the other middlewares in terms of latency and computation time.

Further progress towards a home robot companion for people with mild cognitive impairment

This paper presents results of the development of a socially assistive home robot companion for older people suffering from mild cognitive impairment (MCI) and living (alone) at home. This work was part of the European FP7 project “CompanionAble” (2008-2012) [1] which aimed at developing assistive technologies that can support these elderly and help them to remain in their familiar living environment for as long as possible. To overcome current market entry barriers, from the start we consistently adopted a user- and application-centered development process of the companion robot and focused on three main aspects: (i) the realization of a set of mandatory functionalities to support care recipients and caregivers, (ii) a strict design and usability driven realization to increase the acceptance of the robot by the different end-user groups (the elderly, their relatives, and caregivers), and (iii) the development and component selection considering production and operational costs. In continuation of the work presented in [2], this paper describes the final implementation of the companion robot and presents latest results of functional tests and early findings of user studies recently conducted in the smart house of the Dutch project partner Smart Homes in Eindhoven, The Netherlands.

I'll keep an eye on you: Home robot companion for elderly people with cognitive impairment

The paper gives an overview of the progress in developing a socially assistive home robot companion for elderly people with mild cognitive impairment (MCI) living alone at home. The spectrum of required assistive functionalities of such a robot companion is broad and reaches from reminding functions (e.g. taking medication or drinking) and cognitive stimulation exercises, via mobile videophony with relatives or caregivers, up to the detection and evaluation of critical situations, like falls. The paper is addressing several aspects of our work as part of the European FP7 project “CompanionAble”, as for example the developed robot hardware and its software and control architecture, the implemented skills for robust user detection and tracking and user-centered navigation in the home environment, and reports on already conducted and still ongoing functionality testings and pending usability studies with the end-user target groups (the elderly, relatives, caregivers).

Finding the adequate resolution for grid mapping - Cell sizes locally adapting on-the-fly

For robot mapping occupancy grid maps are the most common representation of the environment. However, most existing algorithms for creating such maps assume a fixed resolution of the grid cells. In this paper we present a novel mapping technique that chooses the resolution of each cell adaptively by merging and splitting cells depending on the measurements. The splitting of the cells is based on a statistical measure that we derive in this paper. In contrast to other approaches the adaption of the resolution is done online during the mapping process itself. Additionally, we introduce the Nd-Tree, a generalization of quadtrees and octrees that allows to subdivide any d-dimensional volume recursively with Nd children per node. Using this data structure our approach can be implemented in a very generic way and allows the creation of 2D, 3D and even higher dimensional maps using the same algorithm. Finally, we show results of our proposed method for 2D and 3D mapping using different kinds of range sensors.

Mobile Robotic Rehabilitation Assistant for walking and orientation training of Stroke Patients: A report on work in progress

As report on work in progress, this paper describes the objectives and the current state of implementation of the ongoing research project ROREAS (Robotic Rehabilitation Assistant for Stroke Patients), which aims at developing a robotic rehabilitation assistant for walking and orientation exercising in self-training during clinical stroke follow-up care. This requires strongly user-centered, polite and attentive social navigation and interaction behaviors that can motivate the patients to start, continue, and regularly repeat their self-training. Against this background, the paper gives an overview of the constraints and requirements arising from the rehabilitation scenario and the operational environment, a heavily populated multi-level rehabilitation center, and presents the robot platform ROREAS which is currently used for developing the demonstrators (walking coach and orientation coach). Moreover, it gives an overview of the robots functional system architecture and presents selected advanced navigation and HRI functionalities required for a personal robotic trainer that can successfully operate in such a challenging real-world environment, up to the results of ongoing functionality tests and upcoming user studies.

Attention-driven monocular scene reconstruction for obstacle detection, robot navigation and map building

In this paper, we present a feature-based approach for monocular scene reconstruction based on Extended Kalman Filters (EKF). Our method processes a sequence of images taken by a single camera mounted frontally on a mobile robot. Using a combination of various techniques, we are able to produce a precise reconstruction that is free from outliers and can therefore be used for reliable obstacle detection and 3D map building. Furthermore, we present an attention-driven method that focuses the feature selection to image areas where the obstacle situation is unclear and where a more detailed scene reconstruction is necessary. In extensive real-world field tests we show that the presented approach is able to detect obstacles that are not seen by other sensors, such as laser range finders. Furthermore, we show that visual obstacle detection combined with a laser range finder can increase the detection rate of obstacles considerably, allowing the autonomous use of mobile robots in complex public and home environments.

Generic NDT mapping in dynamic environments and its application for lifelong SLAM

In this paper, we present a new, generic approach for Simultaneous Localization and Mapping (SLAM). First of all, we propose an abstraction of the underlying sensor data using Normal Distribution Transform (NDT) maps that are suitable for making our approach independent from the used sensor and the dimension of the generated maps. We present several modifications for the original NDT mapping to handle free-space measurements explicitly. We additionally describe a method to detect and handle dynamic objects such as moving persons. This enables the usage of the proposed approach in highly dynamic environments. In the second part of this paper we describe our graph-based SLAM approach that is designed for lifelong usage. Therefore, the memory and computational complexity is limited by pruning the pose graph in an appropriate way. We present a new mapping approach that combines normal distribution transform (NDT) and occupancy mapping.The mapping approach is fully generic and suitable for 2D and 3D mapping with different sensors.We describe a method for detecting and handling dynamic objects to allow mapping in highly dynamic environments.Based on the mapping algorithm a graph based SLAM algorithm is described.The presented SLAM approach allows lifelong mapping and localization in real world applications.