Multiple target tracking based on particle filtering for safety in industrial robotic cells

A. Ibarguren; I. Maurtua; M. A. Pérez; B. Sierra

doi:10.1016/j.robot.2015.05.004

Multiple target tracking based on particle filtering for safety in industrial robotic cells

A. Ibarguren^*
, I. Maurtua
, M. A. Pérez
, B. Sierra

^*Corresponding author for this work

TEKNIKER

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

Human-robot collaboration is a key issue for the development of factories of the future, a space where humans and robots can work and carry out tasks together. Within this collaborative human-robot interaction paradigm, safety is one of most critical subjects. The presented paper describes a security framework for industrial robotic cells based on laser rangefinders able to detect and track obstacles around the robot, information that is used to modify robot's behaviour and guarantee safety. The system includes a Joint Probability Data Association Particle Filter to enhance the tracking process. The obtained results, implemented and tested in a real industrial robotic cell, show the suitability of the approach.

Original language	English
Pages (from-to)	105-113
Number of pages	9
Journal	Robotics and Autonomous Systems
Volume	72
DOIs	https://doi.org/10.1016/j.robot.2015.05.004
Publication status	Published - 1 Oct 2015
Externally published	Yes

Keywords

Particle filter
Robotics
Security
Tracking

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.robot.2015.05.004

Cite this

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title = "Multiple target tracking based on particle filtering for safety in industrial robotic cells",

abstract = "Human-robot collaboration is a key issue for the development of factories of the future, a space where humans and robots can work and carry out tasks together. Within this collaborative human-robot interaction paradigm, safety is one of most critical subjects. The presented paper describes a security framework for industrial robotic cells based on laser rangefinders able to detect and track obstacles around the robot, information that is used to modify robot's behaviour and guarantee safety. The system includes a Joint Probability Data Association Particle Filter to enhance the tracking process. The obtained results, implemented and tested in a real industrial robotic cell, show the suitability of the approach.",

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author = "A. Ibarguren and I. Maurtua and P{\'e}rez, \{M. A.\} and B. Sierra",

year = "2015",

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day = "1",

doi = "10.1016/j.robot.2015.05.004",

language = "English",

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journal = "Robotics and Autonomous Systems",

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TY - JOUR

T1 - Multiple target tracking based on particle filtering for safety in industrial robotic cells

AU - Ibarguren, A.

AU - Maurtua, I.

AU - Pérez, M. A.

AU - Sierra, B.

PY - 2015/10/1

Y1 - 2015/10/1

N2 - Human-robot collaboration is a key issue for the development of factories of the future, a space where humans and robots can work and carry out tasks together. Within this collaborative human-robot interaction paradigm, safety is one of most critical subjects. The presented paper describes a security framework for industrial robotic cells based on laser rangefinders able to detect and track obstacles around the robot, information that is used to modify robot's behaviour and guarantee safety. The system includes a Joint Probability Data Association Particle Filter to enhance the tracking process. The obtained results, implemented and tested in a real industrial robotic cell, show the suitability of the approach.

AB - Human-robot collaboration is a key issue for the development of factories of the future, a space where humans and robots can work and carry out tasks together. Within this collaborative human-robot interaction paradigm, safety is one of most critical subjects. The presented paper describes a security framework for industrial robotic cells based on laser rangefinders able to detect and track obstacles around the robot, information that is used to modify robot's behaviour and guarantee safety. The system includes a Joint Probability Data Association Particle Filter to enhance the tracking process. The obtained results, implemented and tested in a real industrial robotic cell, show the suitability of the approach.

KW - Particle filter

KW - Robotics

KW - Security

KW - Tracking

UR - https://www.scopus.com/pages/publications/84937513825

U2 - 10.1016/j.robot.2015.05.004

DO - 10.1016/j.robot.2015.05.004

M3 - Article

AN - SCOPUS:84937513825

SN - 0921-8890

VL - 72

SP - 105

EP - 113

JO - Robotics and Autonomous Systems

JF - Robotics and Autonomous Systems

ER -

Multiple target tracking based on particle filtering for safety in industrial robotic cells

Abstract

Keywords

UN SDGs

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