PARC: A Plan and Activity Recognition Component for Assistive Robots

Massardi, Jean; Gravel, Mathieu; Beaudry, Éric

doi:10.1109/icra40945.2020.9196856

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…Regarding the speed, these algorithms have been executed in real time at 20 FPS [ 51 ]. For their implementation, computers with basic [ 51 ] and advanced [ 50 ] hardware were used, as well as the robotic platforms Brian [ 47 ] and Pepper [ 49 ].…”

Section: Discussion and Conclusionmentioning

confidence: 99%

“…A double-layer network (CNN and LSTM) was implemented to recognize the following activities: brushing teeth, chopping, drinking water, opening pill container, relaxing on the couch, rinsing the mouth with water, stirring, talking on the couch, talking on the phone, wearing contact lenses, working on the computer, and writing on a whiteboard. Additionally, Massardi et al in [ 50 ] presented the PARC algorithm for an assistance robot to recognize and help people with cognitive or physical disabilities to perform ADLs: (a) an RGB-D camera was implemented to extract the body and objects utilizing the YOLO framework; (b) they calculated whether an object was in the person’s hand to identify the activity; (c) they used a particle filter algorithm to plan the sequence of tasks that the user must perform to complete the activity.…”

Section: Algorithms Used For the Bodymentioning

confidence: 99%

See 1 more Smart Citation

Artificial Vision Algorithms for Socially Assistive Robot Applications: A Review of the Literature

Montaño-Serrano

Jacinto‐Villegas

Vilchis-González

et al. 2021

Sensors

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Today, computer vision algorithms are very important for different fields and applications, such as closed-circuit television security, health status monitoring, and recognizing a specific person or object and robotics. Regarding this topic, the present paper deals with a recent review of the literature on computer vision algorithms (recognition and tracking of faces, bodies, and objects) oriented towards socially assistive robot applications. The performance, frames per second (FPS) processing speed, and hardware implemented to run the algorithms are highlighted by comparing the available solutions. Moreover, this paper provides general information for researchers interested in knowing which vision algorithms are available, enabling them to select the one that is most suitable to include in their robotic system applications.

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Section: Discussion and Conclusionmentioning

confidence: 99%

Section: Algorithms Used For the Bodymentioning

confidence: 99%

Artificial Vision Algorithms for Socially Assistive Robot Applications: A Review of the Literature

Montaño-Serrano

Jacinto‐Villegas

Vilchis-González

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…In [46], by means of RGB-D cameras, an algorithm implemented on a Pepper robot aimed to identify daily activities in a person's life, such as the following: talking on the phone, drinking water, rinsing one's mouth with water, writing on a blackboard, brushing one's teeth, opening a pill container, stirring, relaxing on the couch, working on a computer, and wearing contact lenses. Jean Massardi [47] implemented an algorithm called PARC on a personal assistance robot which aimed to help people with disabilities to complete daily activities successfully.…”

Section: Assistive Robotsmentioning

confidence: 99%

“…with people [44] Recognize gestures Assistance Real Time RGB [45] Face detection Assistance 10 fps N/A [46] Home care Assistance, Rehabilitation N/A RGB-D [47] Recognition of activities Assistance, Rehabilitation Real Time RGB-D An analysis between the years 1971 and 2022 is performed in Figure 6 to show th level of interest in autonomous assistive robots in the database provided by Scopus. Sin 2003, the level of interest in this field has increased.…”

Section: Refsmentioning

confidence: 99%

Autonomous Robots for Services—State of the Art, Challenges, and Research Areas

Misaros

Stan

Donca

et al. 2023

Sensors

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It has been almost half a century since the first interest in autonomous robots was shown, and research is still continuing to improve their ability to make perfectly conscious decisions from a user safety point of view. These autonomous robots are now at a fairly advanced level, which means that their adoption rate in social environments is also increasing. This article reviews the current state of development of this technology and highlights the evolution of interest in it. We analyze and discuss specific areas of its use, for example, its functionality and current level of development. Finally, challenges related to the current level of research and new methods that are still being developed for the wider adoption of these autonomous robots are highlighted.

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