ENRICHME: Perception and Interaction of an Assistive Robot for the Elderly at Home

Coşar, Serhan; Fernández-Carmona, Manuel; Agrigoroaie, Roxana; Pagès, Jordi; Ferland, François; Zhang, Feng; Yue, Shigang; Bellotto, Nicola; Tapus, Adriana

doi:10.1007/s12369-019-00614-y

Cited by 85 publications

(84 citation statements)

References 50 publications

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“…To reduce the computational load, the detector first runs a ground plane estimation to determine a region of interest, which is the most suitable to detect the upper bodies of a standing or walking person. In [58], a mobile robot equipped with an RGB-D camera is used to detect people. Munaro and Menegatti [156] proposed a real-time detection and tracking system based on RGB-D camera data capable of detecting people within groups or standing near walls.…”

Section: Other Detection Models A) Spatio-temporal Featuresmentioning

confidence: 99%

Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking

Camara

Bellotto

Coşar

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part I of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychology models, from the perspective of an AV designer. This self-contained Part I covers the lower levels of this stack, from sensing, through detection and recognition, up to tracking of pedestrians. Technologies at these levels are found to be mature and available as foundations for use in high-level systems, such as behaviour modelling, prediction and interaction control.

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Section: Other Detection Models A) Spatio-temporal Featuresmentioning

confidence: 99%

Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking

Camara

Bellotto

Coşar

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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“…A number of research projects have developed solutions, comprising a diverse set of functionalities, from more specific ones [ 10 , 11 ], to general systems [ 7 , 8 , 12 ], to initiatives (e.g., STRANDS [ 13 ]) that support development of technologies for long-term autonomy of robots.…”

Section: Related Workmentioning

confidence: 99%

“…Another relevant factor of analysis is the robot hardware itself, as well as its price. While some projects [ 6 , 7 ] develop custom built robots, in the attempt to keep the price tag below 15 k EUR, others (see, e.g., in [ 8 ]) focus on exploiting the advantages of more powerful, but far more expensive robots, selling for upward of 35k EUR.…”

Section: Introductionmentioning

confidence: 99%

The AMIRO Social Robotics Framework: Deployment and Evaluation on the Pepper Robot

Ghita

Gavril

Nan

et al. 2020

Sensors

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Recent studies in social robotics show that it can provide economic efficiency and growth in domains such as retail, entertainment, and active and assisted living (AAL). Recent work also highlights that users have the expectation of affordable social robotics platforms, providing focused and specific assistance in a robust manner. In this paper, we present the AMIRO social robotics framework, designed in a modular and robust way for assistive care scenarios. The framework includes robotic services for navigation, person detection and recognition, multi-lingual natural language interaction and dialogue management, as well as activity recognition and general behavior composition. We present AMIRO platform independent implementation based on a Robot Operating System (ROS). We focus on quantitative evaluations of each functionality module, providing discussions on their performance in different settings and the possible improvements. We showcase the deployment of the AMIRO framework on a popular social robotics platform—the Pepper robot—and present the experience of developing a complex user interaction scenario, employing all available functionality modules within AMIRO.

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“…Presently, there are some relevant projects in this field, such as Pearl [3], from Nursebot project, which mainly reminds the user of the daily activities to be carried out, and guides him/her through the environment. Another SAR system is ENRICHME [4], which uses an customized version of the TIAGo robot, and its main goal is to provide home assistance, health monitoring, complementary care, and social support to improve the quality of life of the elderly person. SARDAM, the prototype proposed in this paper, is a monitoring system of the daily routine of an elderly person that uses the NAO robot.…”

Section: Introductionmentioning

confidence: 99%

SARDAM: Service Assistant Robot for Daily Activity Monitoring

Lamas¹,

Bellas²,

Guijarro-Berdiñas³

2020

3rd XoveTIC Conference

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In this work, we propose an autonomous monitoring system for the daily routine of an elderly person. SARDAM (Service Assistant Robot for Daily Activity Monitoring), which is the name of this system, uses a humanoid robot as a key element that carries out a direct interaction with the user. The purpose of SARDAM is to keep the user active as long as possible by suggesting, and monitoring, a series of daily tasks and healthy habits according to the prescription of a health professional, in order to reduce the early appearance of cognitive and motor impairment. In the current version of SARDAM we use the NAO humanoid robot, which performs a natural interaction with the user through vision and speech libraries. To assure the appropriate execution of the user’s daily tasks, a module for emotion detection has been incorporated in order to propose corrective tasks according to the detected emotion. SARDAM was tested in a scenario with a real user, getting successful results and positive opinions from them that encourage further work.

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ENRICHME: Perception and Interaction of an Assistive Robot for the Elderly at Home

Cited by 85 publications

References 50 publications

Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking

Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking

The AMIRO Social Robotics Framework: Deployment and Evaluation on the Pepper Robot

SARDAM: Service Assistant Robot for Daily Activity Monitoring

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