Markus Bajones

Learning and Detecting Objects with a Mobile Robot to Assist Older Adults in Their Homes

Older adults reported that a robot in their homes would be of great help if it could find objects that users regularly search for. We propose an interactive method to learn objects directly with the user and the robot and then use the RGB-D model to search for the object in the scene. The robot presents a turntable to the user for rotating the part in front of its camera and obtain a full 3D model. The user is asked to turn the object upside down and the two half-models are merged. The model is then used at predefined search locations for detecting the object on tables or other horizontal surfaces. Experiments in three environments, up to 14 objects and a total of 1080 scenes indicate that present detection methods need to be considerably improved to provide a good service to users. We analyse the results and contribute to the discussion on how to overcome limited image quality and resolution by exploiting the robotic system.

Hobbit: Providing Fall Detection and Prevention for the Elderly in the Real World

We present the robot developed within the Hobbit project, a socially assistive service robot aiming at the challenge of enabling prolonged independent living of elderly people in their own homes. We present the second prototype (Hobbit PT2) in terms of hardware and functionality improvements following first user studies. Our main contribution lies within the description of all components developed within the Hobbit project, leading to autonomous operation of 371 days during field trials in Austria, Greece, and Sweden. In these field trials, we studied how 18 elderly users (aged 75 years and older) lived with the autonomously interacting service robot over multiple weeks. To the best of our knowledge, this is the first time a multifunctional, low-cost service robot equipped with a manipulator was studied and evaluated for several weeks under real-world conditions. We show that Hobbit’s adaptive approach towards the user increasingly eased the interaction between the users and Hobbit. We provide lessons learned regarding the need for adaptive behavior coordination, support during emergency situations, and clear communication of robotic actions and their consequences for fellow researchers who are developing an autonomous, low-cost service robot designed to interact with their users in domestic contexts. Our trials show the necessity to move out into actual user homes, as only there can we encounter issues such as misinterpretation of actions during unscripted human-robot interaction.

Enabling Long-term Human-Robot Interaction through Adaptive Behavior Coordination

Robots in domestic environments currently perform simple tasks such as floor cleaning in a fully autonomous fashion with great success. During those tasks the lack of human-robot interaction (HRI) is given by design, but is also limiting the robots activities when an unforeseen situation occurs. Based on state-of-the art research in attention methods and sliding autonomy of social robots, we develop a behavior modeling framework, for the recognition of situations that the robot can not mitigate autonomously and the introduction of the user as a partner in the chosen mitigation strategy. We have already explored support for elderly in their homes over the course of three weeks with a fully autonomous robot, during which we discovered the need for adaptive autonomy and behavior. The developed framework will be evaluated in a further study, to show if it can be used across different robots without being penalized by the users after the robot needed assistance, which we see as a must to overcome the novelty effect to further enable long-term HRI in domestic environments.

Robot Navigation in Domestic Environments: Experiences Using RGB-D Sensors in Real Homes

Future home and service robots will require advanced navigation and interaction capabilities. In particular, domestic environments present open challenges that are hard to identify by conducting controlled tests in home-like settings: there is the need to test and evaluate navigation in the actual homes of users. This paper presents the experiences of operating a mobile robot with manipulation capabilities and an open set of tasks in extensive trials with real users, in their own homes. The main difficulties encountered are the requirement to move safely in cluttered 3D environments, the problems related to navigation in narrow spaces, and the need for an adaptive rather than fixed way to approach the users. We describe our solutions based on RGB-D perception and evaluate the integrated system for navigation in real home environments, pointing out remaining challenges towards more advanced commercial solutions.

Investigating the Influence of Culture on Helping Behavior Towards Service Robots

When interaction with robots, peoples cultural background show an impact on the robots expected behavior, depending on how common robots are in these cultures. Such impact is especially notable when a robot is not able to fulfill a task and needs support from a user. We report the results of an online-based survey, investigating the effect of cultural differences between participants from Austria, Japan and the USA. Our results show that in such situations the robots behavior needs to adapt to the users cultural background.