Why socially assistive robots?

Robots are becoming part of our daily living. The next generation of robots include autonomous cars, context-aware vacuum cleaners, smart house devices, collaborative wheelchairs, etc. Some of these robots are designed to engage people around in social interactions, or even collaborate with them in solving different tasks. These social robots face more complex technical challenges regarding perceptual and motor capabilities, cognitive processing and adaptability. They deal with more demanding safety issues. Finally, they also open a delicate ethical dilemma regarding its use. Hence, answering the question why using a social robot? becomes a mandatory prerequisite to use them. This talk addresses this question for a subset of social robots: socially assistive robots. These robots focus on assisting people through social interaction in daily life environments (i.e. houses, nursing homes, etc.). They are part of the technologies for Assisted Living, a key concept in the upcoming silver society. The motivation to use them is based on a set of features: there are many therapies and rehabilitation processes that require social interaction, instead of physical contact. Socially assistive robots can be proactive, looking for people, starting interactions, sharing information, remembering and proposing events or activities. Finally, people are more motivated to interact with physically embodied agents (people, pets, robots) than with screens. All these benefits have driven an important R+D effort involving companies and institutions worldwide, and socially assistive robots are becoming an interesting business opportunity. However, there are still open key questions related to cost, safety, acceptability and usability of socially assistive robots. Moreover, these items have still to be evaluated in long term experiments. This talk details the current advances and future work towards solving these questions in the framework of the ECHORD++ EU project CLARC.Para recibir financiación, debo incluir en este campo: Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

CLARK - Smart Clinic Assistant Robot for CGA

En esta presentación se exponen la arquitectura general y el estado actual de desarrollo del sistema CLARK. Dicho sistema tiene como objetivo el despliegue de un asistente robótico para ayudar a un médico en la realización de procedimientos CGA (Comprehensive Geriatric Assessment), de forma que ciertas tareas, tales como la realización de cuestionarios o pruebas de movimiento, puedan ser realizadas por el robot de forma paralela al resto del procedimiento CGA, aumentando así su eficiencia.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Multi-feature Bottom-up Processing and Top-down Selection for an Object-based Visual Attention Model

Artificial vision systems can not process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. However, inspired by biological perception systems, it is possible to develop an artificial attention model able to select only the relevant part of the scene, as human vision does. This paper presents an attention model which draws attention over perceptual units of visual information, called proto-objects, and which uses a linear combination of multiple low-level features (such as colour, symmetry or shape) in order to calculate the saliency of each of them. But not only bottom-up processing is addressed, the proposed model also deals with the top-down component of attention. It is shown how a high-level task can modulate the global saliency computation, modifying the weights involved in the basic features linear combination.Ministerio de Economía y Competitividad (MINECO), proyectos: TIN2008-06196 y TIN2012-38079-C03-03. Campus de Excelencia Internacional Andalucía Tech

RoboARCH: An autonomous robot for analysis and documentation of historical architectures

The Mediterranean basin has an impressive amount of millenarian urban structures which have been modelled along centuries. Unfortunately, they are sometimes damaged due to both the passage of time as well as bad preservation criteria. In order to avoid these situations or reduce their effects, new preservation criteria have arisen in the last decades. These criteria aim to revitalize the historical value of these architectural remains from a cultural and economic perspective. In this line of research, the “Archaeology of Architecture” applies the theoretical principles of the archaeology to study buildings and streets, offering new methodologies of analysis. An important part of these methodologies incorporates new technologies, such as 3D scanners, robotic total stations, or virtual and augmented reality, to the data acquisition and processing tasks. The application of these technologies in the area of Historical Heritage results in a breakthrough in the graphic documentation of monuments and archaeological remains, which allows the development of new preservation strategies. Among all these new technologies, this abstract proposes the use of an autonomous robot to help identifying elements inside a building. The robot navigates through the environment, collects data and compares them against well-known historical and architectural archetypes, to find a set of candidates for each perceived pattern. The advantages of the proposed system when compared against current state-of-the-art techniques are the following: (i) the robot explores the environment autonomously using SLAM (Simultaneous Localization And Mapping) algorithms and acquires colour and depth information; (ii) no special markers, such as the targets or spheres usually employed by robotic total stations, are required; (iii) the system uses advanced image processing methods to automatically provide a first characterization of perceived borders, that will help in different identification processes, from single elements to more complex structures; (iv) obtained data are compared against historical and architectural archetypes included in a data base; (v) evaluation of the object position inside the stratigraphic sequence of the wall.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Integration of the Alexa assistant as a voice interface for robotics platforms

Virtual assistants such as Cortana or Google Assistant are becoming familiar devices in everyday environments, where they are used to control real devices through natural language. This paper extends this application scenario, and it describes the use of the Alexa assistant from Amazon through an Echo dot device to drive the behaviour of a robotic platform. The paper focuses on the description of the technologies employed to set such ecosystem. Significantly, the proposed architecture is based, from the remote server to the on-board controllers, in LowEnergy (LE) hardware and a scalable software platform. This approach will ease programmers integrating different platforms, e.g. mobile-based applications to control robots or home-made devices.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

From perception to action and vice versa: a new architecture showing how perception and action can modulate each other simultaneously

Presentado en: 6th European Conference on Mobile Robots (ECMR) Sep 25-27, 2013 Barcelona, SpainArtificial vision systems can not process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. However, inspired by biological perception systems, it is possible to develop an artificial attention model able to select only the relevant part of the scene, as human vision does. From the Automated Planning point of view, a relevant area can be seen as an area where the objects involved in the execution of a plan are located. Thus, the planning system should guide the attention model to track relevant objects. But, at the same time, the perceived objects may constrain or provide new information that could suggest the modification of a current plan. Therefore, a plan that is being executed should be adapted or recomputed taking into account actual information perceived from the world. In this work, we introduce an architecture that creates a symbiosis between the planning and the attention modules of a robotic system, linking visual features with high level behaviours. The architecture is based on the interaction of an oversubscription planner, that produces plans constrained by the information perceived from the vision system, and an object-based attention system, able to focus on the relevant objects of the plan being executed.Spanish MINECO projects TIN2008-06196, TIN2012-38079-C03-03 and TIN2012-38079-C03-02. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

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

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