Evidence map›Paper›PMID 35890940›Full record

ArticleSensors (Basel, Switzerland)2022

Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments.

Andrea Eirale, Mauro Martini, Luigi Tagliavini, Dario Gandini, Marcello Chiaberge, Giuseppe Quaglia

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Method for Bottle Opening with a Dual-Arm Robot.Biomimetics (Basel, Switzerland) · 2024
    Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Andrea EiraleDepartment of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0003-4172-0365
Mauro MartiniDepartment of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0002-6204-3845
Luigi TagliaviniDepartment of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0001-8925-0417
Dario GandiniDepartment of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0002-5013-7561
Marcello ChiabergeDepartment of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0002-1921-0126
Giuseppe QuagliaDepartment of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0003-4951-9228

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population aging and pandemics have been shown to cause the isolation of elderly people in their houses, generating the need for a reliable assistive figure. Robotic assistants are the new frontier of innovation for domestic welfare, and elderly monitoring is one of the services a robot can handle for collective well-being. Despite these emerging needs, in the actual landscape of robotic assistants, there are no platforms that successfully combine reliable mobility in cluttered domestic spaces with lightweight and offline Artificial Intelligence (AI) solutions for perception and interaction. In this work, we present Marvin, a novel assistive robotic platform we developed with a modular layer-based architecture, merging a flexible mechanical design with cutting-edge AI for perception and vocal control. We focus the design of Marvin on three target service functions: monitoring of elderly and reduced-mobility subjects, remote presence and connectivity, and night assistance. Compared to previous works, we propose a tiny omnidirectional platform, which enables agile mobility and effective obstacle avoidance. Moreover, we design a controllable positioning device, which easily allows the user to access the interface for connectivity and extends the visual range of the camera sensor. Nonetheless, we delicately consider the privacy issues arising from private data collection on cloud services, a critical aspect of commercial AI-based assistants. To this end, we demonstrate how lightweight deep learning solutions for visual perception and vocal command can be adopted, completely running offline on the embedded hardware of the robot.

Indexed as

RoboticsRobotic Surgical ProceduresAgedArtificial IntelligenceHumansArtificial Intelligenceassistive indoor roboticsmobile roboticsmodularitysystem designvocal assistant

Identifiers

PMID35890940
PMCPMC9322347

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.