Literature DB >> 33668162

Human-Robot Perception in Industrial Environments: A Survey.

Andrea Bonci1, Pangcheng David Cen Cheng2, Marina Indri2, Giacomo Nabissi1, Fiorella Sibona2.   

Abstract

Perception capability assumes significant importance for human-robot interaction. The forthcoming industrial environments will require a high level of automation to be flexible and adaptive enough to comply with the increasingly faster and low-cost market demands. Autonomous and collaborative robots able to adapt to varying and dynamic conditions of the environment, including the presence of human beings, will have an ever-greater role in this context. However, if the robot is not aware of the human position and intention, a shared workspace between robots and humans may decrease productivity and lead to human safety issues. This paper presents a survey on sensory equipment useful for human detection and action recognition in industrial environments. An overview of different sensors and perception techniques is presented. Various types of robotic systems commonly used in industry, such as fixed-base manipulators, collaborative robots, mobile robots and mobile manipulators, are considered, analyzing the most useful sensors and methods to perceive and react to the presence of human operators in industrial cooperative and collaborative applications. The paper also introduces two proofs of concept, developed by the authors for future collaborative robotic applications that benefit from enhanced capabilities of human perception and interaction. The first one concerns fixed-base collaborative robots, and proposes a solution for human safety in tasks requiring human collision avoidance or moving obstacles detection. The second one proposes a collaborative behavior implementable upon autonomous mobile robots, pursuing assigned tasks within an industrial space shared with human operators.

Entities:  

Keywords:  3D sensors; collision avoidance; collision detection; human action recognition; human-robot collaboration; human-robot perception; machine vision; robot guidance

Year:  2021        PMID: 33668162     DOI: 10.3390/s21051571

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  4 in total

1.  Digital Twin-Driven Human Robot Collaboration Using a Digital Human.

Authors:  Tsubasa Maruyama; Toshio Ueshiba; Mitsunori Tada; Haruki Toda; Yui Endo; Yukiyasu Domae; Yoshihiro Nakabo; Tatsuro Mori; Kazutsugu Suita
Journal:  Sensors (Basel)       Date:  2021-12-10       Impact factor: 3.576

2.  A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction.

Authors:  Fahad Iqbal Khawaja; Akira Kanazawa; Jun Kinugawa; Kazuhiro Kosuge
Journal:  Sensors (Basel)       Date:  2021-12-09       Impact factor: 3.576

3.  My Caregiver the Cobot: Comparing Visualization Techniques to Effectively Communicate Cobot Perception to People with Physical Impairments.

Authors:  Max Pascher; Kirill Kronhardt; Til Franzen; Uwe Gruenefeld; Stefan Schneegass; Jens Gerken
Journal:  Sensors (Basel)       Date:  2022-01-19       Impact factor: 3.576

4.  Development of an Integrated Virtual Reality System with Wearable Sensors for Ergonomic Evaluation of Human-Robot Cooperative Workplaces.

Authors:  Teodorico Caporaso; Stanislao Grazioso; Giuseppe Di Gironimo
Journal:  Sensors (Basel)       Date:  2022-03-21       Impact factor: 3.576

  4 in total

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