Adriana Tapus

Socially assistive robotics [Grand Challenges of Robotics]

Socially intelligent robotics is the pursuit of creating robots capable of exhibiting natural-appearing social qualities. Beyond the basic capabilities of moving and acting autonomously, the field has focused on the use of the robots physical embodiment to communicate and interact with users in a social and engaging manner. One of its components, socially assistive robotics, focuses on helping human users through social rather than physical interaction. Early results already demonstrate the promises of socially assistive robotics, a new interdisciplinary research area with large horizons of fascinating and much needed research. Even as socially assistive robotic technology is still in its early stages of development, the next decade promises systems that will be used in hospitals, schools, and homes in therapeutic programs that monitor, encourage, and assist their users. This is an important time in the development of the field, when the board technical community and the beneficiary populations must work together to shape the field toward its intended impact on improved human quality of life

User-Robot Personality Matching and Assistive Robot Behavior Adaptation for Post-Stroke Rehabilitation Therapy

This paper describes a hands-off socially assistive therapist robot designed to monitor, assist, encourage, and socially interact with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion–introversion of the robot and the user. We also demonstrate a behavior adaptation system capable of adjusting its social interaction parameters (e.g., interaction distances/proxemics, speed, and vocal content) toward customized post-stroke rehabilitation therapy based on the user’s personality traits and task performance. Three validation experiment sets are described. The first maps the user’s extroversion–introversion personality dimension to a spectrum of robot therapy styles that range from challenging to nurturing. The second and the third experiments adjust the personality matching dynamically to adapt the robot’s therapy styles based on user personality and performance. The reported results provide first evidence for user preference for personality matching in the assistive domain and demonstrate how the socially assistive robot’s autonomous behavior adaptation to the user’s personality can result in improved human task performance.

Incremental robot mapping with fingerprints of places

Even today, robot mapping is one of the biggest challenges in mobile robotics. Geometric or topological maps can be used by a robot to navigate in the environment. Automatic creation of such maps is still problematic if the robot tries to map large environments. This paper presents a new method for incremental mapping using fingerprints of places. This type of representation permits a reliable, compact, and distinctive environment-modeling and makes navigation and localization easier for the robot. Experimental results for incremental mapping using a mobile robot equipped with a multi-sensor system composed of two 180/spl deg/ laser range finders and an omni-directional camera are also reported.

The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia

Currently the 2 percent growth rate for the worlds older population exceeds the 1.2 rate for the worlds population as a whole. By 2050, the number of individuals over the age 85 is projected to be three times more than there is today. Most of these individuals will need physical, emotional, and cognitive assistance. In this paper, we present a new adaptive robotic system based on the socially assistive robotics (SAR) technology that tries to provide a customized help protocol through motivation, encouragements, and companionship to users suffering from cognitive changes related to aging and/or Alzheimers disease. Our results show that this approach can engage the patients and keep them interested in interacting with the robot, which, in turn, increases their positive behavior.

Simultaneous localization and odometry calibration for mobile robot

This paper presents both the theory and the first experimental results of a new method which allows simultaneous estimation of the robot configuration and the odometry error (both systematic and non-systematic) during the mobile robot navigation. The estimation of the non-systematic components is carried out through an augmented Kalman filter which estimates a state containing the robot configuration and the parameters of the odometry error. It uses encoder readings as inputs and the readings from a laser range finder as observations. The estimation of the non-systematic components is carried out through another Kalman filter where the observations are obtained by two subsequent robot configurations provided by the previous augmented Kalman filter.

User Personality Matching with a Hands-Off Robot for Post-stroke Rehabilitation Therapy

This paper describes a hands-off therapist robot that monitors, assists, encourages, and socially interacts with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion-introversion of the robot and the user. The experiments map the extroversion-introversion personality dimension and the spectrum of therapy styles that range from challenging to nurturing. The experimental results provide first evidence for the preference of personality matching in the assistive domain.

Environmental modeling with fingerprint sequences for topological global localization

In this paper a perception approach allowing for high distinctiveness is presented. The method works in accordance to the fingerprint concept. Such representation allows using a very flexible matching approach based on the minimum energy algorithm. The whole extraction and matching approach is presented in details and viewed in a topological optic, where the matching result can directly be used as observation function for a topological localization approach. The experimentation section will validate the fingerprint approach and present different set of experiments in order to explain practically the choice of different types of features.

The role of physical embodiment of a therapist robot for individuals with cognitive impairments

This research focuses on studying the possible role of a socially interactive robot as a tool for monitoring and encouraging cognitive activities of the elderly and/or individuals suffering from dementia. One of the aims of this work is to show the benefits of the robots physical embodiment in human-robot social interactions. The social therapist robot tries to provide customized cognitive stimulation by playing a music game with the user. The results of the 8-month pilot study depict a more efficient, natural, and preferred interaction with the robot rather than with the simulated robot.

Robust vision-based robot localization using combinations of local feature region detectors

This paper presents a vision-based approach for mobile robot localization. The model of the environment is topological. The new approach characterizes a place using a signature. This signature consists of a constellation of descriptors computed over different types of local affine covariant regions extracted from an omnidirectional image acquired rotating a standard camera with a pan-tilt unit. This type of representation permits a reliable and distinctive environment modelling. Our objectives were to validate the proposed method in indoor environments and, also, to find out if the combination of complementary local feature region detectors improves the localization versus using a single region detector. Our experimental results show that if false matches are effectively rejected, the combination of different covariant affine region detectors increases notably the performance of the approach by combining the different strengths of the individual detectors. In order to reduce the localization time, two strategies are evaluated: re-ranking the map nodes using a global similarity measure and using standard perspective view field of 45°.In order to systematically test topological localization methods, another contribution proposed in this work is a novel method to see the degradation in localization performance as the robot moves away from the point where the original signature was acquired. This allows to know the robustness of the proposed signature. In order for this to be effective, it must be done in several, variated, environments that test all the possible situations in which the robot may have to perform localization.

Topological Global Localization and Mapping with Fingerprints and Uncertainty

Navigation in unknown or partially unknown environments remains one of the biggest challenges in today\s mobile robotics. Environmental modeling, perception, localization and mapping are all needed for a successful approach. The contribution of this paper resides in the extension of the fingerprint concept (circular list of features around the robot) with uncertainty modeling, in order to improve localization and allow for automatic map building. The uncertainty is defined as the probability of a feature of being present in the environment when the robot perceives it. The whole approach is presented in details and viewed in a topological optic. Experimental results of the perception and localization capabilities with a mobile robot equipped with two 180° laser range finders and an omni-directional camera are reported.