CLARA: Building a Socially Assistive Robot to Interact with Elderly People

Although the global population is aging, the proportion of potential caregivers is not keeping pace. It is necessary for society to adapt to this demographic change, and new technologies are a powerful resource for achieving this. New tools and devices can help to ease independent living and alleviate the workload of caregivers. Among them, socially assistive robots (SARs), which assist people with social interactions, are an interesting tool for caregivers thanks to their proactivity, autonomy, interaction capabilities, and adaptability. This article describes the different design and implementation phases of a SAR, the CLARA robot, both from a physical and software point of view, from 2016 to 2022. During this period, the design methodology evolved from traditional approaches based on technical feasibility to user-centered co-creative processes. The cognitive architecture of the robot, CORTEX, keeps its core idea of using an inner representation of the world to enable inter-procedural dialogue between perceptual, reactive, and deliberative modules. However, CORTEX also evolved by incorporating components that use non-functional properties to maximize efficiency through adaptability. The robot has been employed in several projects for different uses in hospitals and retirement homes. This paper describes the main outcomes of the functional and user experience evaluations of these experiments.This work has been partially funded by the EU ECHORD++ project (FP7-ICT-601116), the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 825003 (DIH-HERO SUSTAIN), the RoQME and MiRON Integrated Technical Projects funded, in turn, by the EU RobMoSys project (H20202-732410), the project RTI2018-099522-B-C41, funded by the Gobierno de España and FEDER funds, the AT17-5509-UMA and UMA18-FEDERJA-074 projects funded by the Junta de Andalucía, and the ARMORI (CEIATECH-10) and B1-2021_26 projects funded by the University of Málaga. Partial funding for open access charge: Universidad de Málaga

Multimodal object recognition module for social robots

Sensor fusion techniques are able to increase robustness and accuracy over data provided by isolated sensors. Fusion can be performed at a low level, creating shared data representations from multiple sensory inputs, or at a high level, checking consistency and similarity of objects provided by different sources. These last techniques are more prone to discard perceived objects due to overlapping or partial occlusions, but they are usually simpler, and more scalable. Hence, they are more adequate when data gathering is the key requirement, while safety is not compromised, computational resources may be limited and it is important to easily incorporate new sensors (e.g. monitorization in smart environments or object recognition for social robots). This paper proposes a novel perception integrator module that uses low complexity algorithms to implement fusion, tracking and forgetting mechanisms. Its main characteristics are simplicity, adaptability and scalability. The system has been integrated in a social robot and employed to achieve multimodal object and person recognition. Experimental results show the adequacy of the solution in terms of detection and recognition rates, integrability into the constrained resources of a robot, and adaptability to different sensors, detection priorities and scenarios.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

On Managing Knowledge for MAPE-K Loops in Self-Adaptive Robotics Using a Graph-Based Runtime Model

Service robotics involves the design of robots that work in a dynamic and very open environment, usually shared with people. In this scenario, it is very difficult for decision-making processes to be completely closed at design time, and it is necessary to define a certain variability that will be closed at runtime. MAPE-K (Monitor–Analyze–Plan–Execute over a shared Knowledge) loops are a very popular scheme to address this real-time self-adaptation. As stated in their own definition, they include monitoring, analysis, planning, and execution modules, which interact through a knowledge model. As the problems to be solved by the robot can be very complex, it may be necessary for several MAPE loops to coexist simultaneously in the robotic software architecture endowed in the robot. The loops will then need to be coordinated, for which they can use the knowledge model, a representation that will include information about the environment and the robot, but also about the actions being executed. This paper describes the use of a graph-based representation, the Deep State Representation (DSR), as the knowledge component of the MAPE-K scheme applied in robotics. The DSR manages perceptions and actions, and allows for inter- and intra-coordination of MAPE-K loops. The graph is updated at runtime, representing symbolic and geometric information. The scheme has been successfully applied in a retail intralogistics scenario, where a pallet truck robot has to manage roll containers for satisfying requests from human pickers working in the warehousePartial funding for open access charge: Universidad de Málaga. This work has been partially developed within SA3IR (an experiment funded by EU H2020 ESMERA Project under Grant Agreement 780265), the project RTI2018-099522-B-C4X, funded by the Gobierno de España and FEDER funds, and the B1-2021_26 project, funded by the University of Málaga

A General-Purpose Architecture to Control Mobile Robots

This paper at: 15th Workshop of Physical Agent. at took place, June 12 and 13, 2014 in León (Spain)Complex robotic tasks require the coordination of a considerable amount of skills. This is generally achieved generating and executing action plans that fulfill the preconditions of the given objective. These tasks can be highly dynamic, since the appearance of new objects or unexpected situations is a constant during the plan execution. In this context, robot control systems require the capability of managing a suitable world model (creating, removing or retyping dynamically objects as a result of the plan execution), and the capability of monitoring and replanning when unexpected situations are detected. In this paper we introduce a general-purpose architecture for autonomous mobile robots providing these features. The architecture allows to generate planning applications since it integrates planning, re-planning, monitoring and learning capabilities, and, at the same time, manages a consistent graph-like world model. Finally, we present some preliminary results of the deployment of such architecture in an advertisement promoting robot domain.This paper has been partially supported by the Spanish Ministerio de Economía y Competitividad TIN2012-TIN2012-38079 and FEDER funds, and by the Innterconecta Programme 2011 project ITC-20111030 ADAPTA.Publicad

Testing a fully autonomous robotic salesman in real scenarios

Over the past decades, the number of robots deployed in museums, trade shows and exhibitions have grown steadily. This new application domain has become a key research topic in the robotics community. Therefore, new robots are designed to interact with people in these domains, using natural and intuitive channels. Visual perception and speech processing have to be considered for these robots, as they should be able to detect people in their environment, recognize their degree of accessibility and engage them in social conversations. They also need to safely navigate around dynamic, uncontrolled environments. They must be equipped with planning and learning components, that allow them to adapt to different scenarios. Finally, they must attract the attention of the people, be kind and safe to interact with. In this paper, we describe our experience with Gualzru, a salesman robot endowed with the cognitive architecture RoboCog. This architecture synchronizes all previous processes in a social robot, using a common inner representation as the core of the system. The robot has been tested in crowded, public daily life environments, where it interacted with people that had never seen it before nor had a clue about its functionality. Experimental results presented in this paper demonstrate the capabilities of the robot and its limitations in these real scenarios, and define future improvement actions.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The cognitive architecture of a robotic salesman

This paper describes a robotics cognitive architecture for social robots named CORTEX. This architecture integrates di fferent levels of abstraction (from basic geometry to high-level predicates) into a unique Deep Space Representation (DSR) that diff erent agents interface. These agents update the contents of the DSR with new data from the outer world, and execute, plan and design behaviours. The design of CORTEX as an unified deep representation allows to fit both the subsymbolic processing and exibility requirements of robot control. In this paper a first implementation of CORTEX has been integrated into Gualzru, a robotic salesman, and tested in real scenarios. Results show that this cognitive architecture allows this robot to adequately execute its use case, and that it has a promising adaptability to achieve new tasks and be used in new scenarios.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Integrating the users in the design of a robot for making Comprehensive Geriatric Assessments (CGA) to elderly people in care centers

Lisboa, (28-31 de agosto 2017)Comprehensive Geriatric Assessment (CGA) is a multidimensional and multidisciplinary diagnostic instrument that helps provide personalized care to the elderly, by evaluating their physical and mental state. In a social and economic context of growing ageing populations, medical experts can save time and effort if provided with interactive tools to efficiently assist them in doing CGAs, managing standardized tests or data collection. Recent research proposes the use of social robots as the central part of these tools. These robots must be able to unfold all functionalities that questionnaires or motion-based tests require, including natural language, face tracking and monitoring, human motion capture and so on. But another issue is the robot's acceptability and trust by the end-users, both patients (elderly people) and clinicians: the robot needs to be able to engage with the patients during the interaction sessions, and must be perceived as a useful and efficient tool by the clinicians. This paper presents the acquisition of new user requirements for CLARC, through participatory and user-centered design approach, to inform the improvement of both interface and interaction. Thirty eight persons (elderly people, caregivers and health professionals) were involved in the design process of CLARC, based on user-centered methods and techniques of Human-Computer Interaction discipline.This work has been partially funded by the European Union ECHORD++ project (FP7-ICT-601116) and the TIN2015-65686-C5-1-R Spanish Ministerio de EconomÍa y Competitividad project and FEDER funds

Percepts symbols or Action symbols? Generalizing how all modules interact within a software architecture for cognitive robotics

Robots require a close coupling of perception and action. Cognitive robots go beyond this to require a further coupling with cognition. From the perspective of robotics, this coupling generally emphasizes a tightly integrated perceptuomotor system, which is then loosely connected to some limited form of cognitive system such as a planner. At the other end, from the perspective of automated planning, the emphasis is on a highly functional system that, taken to its extreme, calls perceptual and motor modules as independent functions. This paper proposes to join both perspectives through a unique representation where the responses of all modules on the software architecture (percepts or actions) are grounded using the same set of symbols. This allows to generalize the signal-to-symbol divide that separates classic perceptuomotor and automated planning systems, being the result a software architecture where all software modules interact using the same tokens.This paper has been partially supported by the Spanish Ministerio de Economía y Competitividad TIN2015-65686-C5 and FEDER funds and by the FP7 EU project ECHORD++ grant 601116 (CLARK project)

CLARC: A cognitive robot for helping geriatric doctors in real scenarios

Third Iberian Robotics Conference (ROBOT 2017). 22 to 24 November 2017, Seville, SpainAbstract: Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate the frailty of elderly persons in order to create therapy plans that improve their quality of life. For robotizing these tests, we are designing and developing CLARC, a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Built around a shared internal representation of the outer world, the architecture is composed of software modules able to plan and generate a stream of actions, to execute actions emanated from the representation or to update this by including/removing items at different abstraction levels. Percepts, actions and intentions coming from all software modules are grounded within this unique representation. This allows the robot to react to unexpected events and to modify the course of action according to the dynamics of a scenario built around the interaction with the patient. The paper describes the architecture of the system as well as the preliminary user studies and evaluation to gather new user requirements.This work has been partially funded by the EU ECHORD++ project (FP7-ICT-601116) and the TIN2015-65686-C5-1-R (MINECO and FEDER funds). Javier García is partially supported by the Comunidad de Madrid (Spain) funds under the project 2016-T2/TIC-171

Adherence and Toxicity during the Treatment of Latent Tuberculous Infection in a Referral Center in Spain

Latent tuberculosis infection; Toxicity; Tuberculosis screeningInfecció tuberculosa latent; Toxicitat; Cribratge de tuberculosiInfección tuberculosa latente; Toxicidad; Cribado de tuberculosisThe screening and treatment of latent tuberculosis infection (LTBI) in countries with a low incidence of TB is a key strategy for the elimination of tuberculosis (TB). However, treatment can result in adverse events (AEs) and have poor adherence. This study aimed to describe treatment outcomes and AEs for LTBI patients at two departments in Vall d'Hebron University Hospital in Barcelona, Spain. A retrospective study was conducted on all persons treated for LTBI between January 2018 and December 2020. Variables collected included demographics, the reason for LTBI screening and treatment initiation, AEs related to treatment, and treatment outcome. Out of 261 persons who initiated LTBI treatment, 145 (55.6%) were men, with a median age of 42.1 years. The indications for LTBI screening were household contact of a TB case in 96 (36.8%) persons, immunosuppressive treatment in 84 (32.2%), and recently arrived migrants from a country with high TB incidence in 81 (31.0%). Sixty-three (24.1%) persons presented at least one AE during treatment, and seven (2.7%) required definitive discontinuation of treatment. In the multivariate analysis, AE development was more frequent in those who started LTBI treatment due to immunosuppression. Overall, 226 (86.6%) completed treatment successfully. We concluded that LTBI screening and treatment groups had different risks for adverse events and treatment outcomes. Persons receiving immunosuppressive treatment were at higher risk of developing AEs, and recently arrived immigrants from countries with a high incidence of TB had greater LTFU. A person-centered adherence and AE management plan is recommended.A.M.L. was supported by a postdoctoral grant “Juan Rodés” (JE21/00027) from the Instituto de Salud Carlos through the Ministry of Economy and Competitiveness, Spain