Dynamic Safety Zones for Industrial Robots: A Fuzzy Logic and Computer Vision Approach

This research focuses on integrating a robotic manipulator in shared workspaces within the framework of Indus-try 4.0 for Human-Robot Collaboration (HRC). The primary objective is to implement a safe strategy by employing a fuzzy-speed controller to enhance the mobile robot's movements near machinery. This strategy utilizes two cameras: one mounted on the ceiling of the industrial environment and another on the robot itself, called an eye-in-hand camera. The You Only Look Once Version 3 (YOLOv3) Convolutional Neural Network (CNN) detects the obstacles in the environment and identifies the target objects. Simulations were conducted using Gazebo software along with a Robot Operating System (ROS) to determine the effectiveness of the proposed approach in ensuring safe robot movements while accurately reaching target positions by dynamically adjusting velocity within the defined danger zone.

Authors

Institutions

Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/sbr/wre63066.2024.10837923
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamic Safety Zones for Industrial Robots: A Fuzzy Logic and Computer Vision Approach

V. Schettino, Milena Faria Pinto, Diego B. Haddad, Tatiana M. B. Santos et al.
1 citations
Industrial Vision Systems and Defect Detection
0.35
article

Dynamic Safety Zones for Industrial Robots: A Fuzzy Logic and Computer Vision Approach

V. Schettino, Milena Faria Pinto, Diego B. Haddad, Tatiana M. B. Santos, Lucas C. Sousa, M. F. Santos
article en
1 citations

Abstract

This research focuses on integrating a robotic manipulator in shared workspaces within the framework of Indus-try 4.0 for Human-Robot Collaboration (HRC). The primary objective is to implement a safe strategy by employing a fuzzy-speed controller to enhance the mobile robot's movements near machinery. This strategy utilizes two cameras: one mounted on the ceiling of the industrial environment and another on the robot itself, called an eye-in-hand camera. The You Only Look Once Version 3 (YOLOv3) Convolutional Neural Network (CNN) detects the obstacles in the environment and identifies the target objects. Simulations were conducted using Gazebo software along with a Robot Operating System (ROS) to determine the effectiveness of the proposed approach in ensuring safe robot movements while accurately reaching target positions by dynamically adjusting velocity within the defined danger zone.

Federal Center for Technological Education Celso Suckow da Fonseca (BR), Universidade Federal Fluminense (BR), Federal Center for Technological Education of Minas Gerais (BR)
Sustainable cities and communities
Openalex Percentile: Top 31%
Industrial Vision Systems and Defect Detection
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Dynamic Safety Zones for Industrial Robots: A Fuzzy Logic and Computer Vision Approach — V. Schettino, Milena Faria Pinto, et al. · (2024) | TGRS Research Map | TGRS