Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction

We develop a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of natural language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art

The CARESSES study protocol: testing and evaluating culturally competent socially assistive robots among older adults residing in long term care homes through a controlled experimental trial

Background : This article describes the design of an intervention study that focuses on whether and to what degree culturally competent social robots can improve health and well-being related outcomes among older adults residing long-term care homes. The trial forms the final stage of the international, multidisciplinary CARESSES project aimed at designing, developing and evaluating culturally competent robots that can assist older people according to the culture of the individual they are supporting. The importance of cultural competence has been demonstrated in previous nursing literature to be key towards improving health outcomes among patients. Method : This study employed a mixed-method, single-blind, parallel-group controlled before-and-after experimental trial design that took place in England and Japan. It aimed to recruit 45 residents of long-term care homes aged ≥65 years, possess sufficient cognitive and physical health and who self-identify with the English, Indian or Japanese culture (n = 15 each). Participants were allocated to either the experimental group, control group 1 or control group 2 (all n = 15). Those allocated to the experimental group or control group 1 received a Pepper robot programmed with the CARESSES culturally competent artificial intelligence (experimental group) or a limited version of this software (control group 1) for 18 h across 2 weeks. Participants in control group 2 did not receive a robot and continued to receive care as usual. Participants could also nominate their informal carer(s) to participate. Quantitative data collection occurred at baseline, after 1 week of use, and after 2 weeks of use with the latter time-point also including qualitative semi-structured interviews that explored their experience and perceptions further. Quantitative outcomes of interest included perceptions of robotic cultural competence, health-related quality of life, loneliness, user satisfaction, attitudes towards robots and caregiver burden. Discussion : This trial adds to the current preliminary and limited pool of evidence regarding the benefits of socially assistive robots for older adults which to date indicates considerable potential for improving outcomes. It is the first to assess whether and to what extent cultural competence carries importance in generating improvements to well-being

What topic do you want to hear about? : A bilingual talking robot using English and Japanese Wikipedias

Peer reviewe

Averting Robot Eyes

Home robots will cause privacy harms. At the same time, they can provide beneficial services—as long as consumers trust them. This Essay evaluates potential technological solutions that could help home robots keep their promises, avert their eyes, and otherwise mitigate privacy harms. Our goals are to inform regulators of robot-related privacy harms and the available technological tools for mitigating them, and to spur technologists to employ existing tools and develop new ones by articulating principles for avoiding privacy harms. We posit that home robots will raise privacy problems of three basic types: (1) data privacy problems; (2) boundary management problems; and (3) social/relational problems. Technological design can ward off, if not fully prevent, a number of these harms. We propose five principles for home robots and privacy design: data minimization, purpose specifications, use limitations, honest anthropomorphism, and dynamic feedback and participation. We review current research into privacy-sensitive robotics, evaluating what technological solutions are feasible and where the harder problems lie. We close by contemplating legal frameworks that might encourage the implementation of such design, while also recognizing the potential costs of regulation at these early stages of the technology