Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stereotype Content Model02:16

Stereotype Content Model

13.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
13.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Size Estimation of Grasped Objects Using a Soft Pneumatic Gripper Integrated with a Piezoresistive CNT/PDMS Sensor.

Micromachines·2026
Same author

Dual Component Framework Approach for Automated Nerve Conduction Study Interpretation: Rule-Based Coding and Fine-Tuned Language Model.

Muscle & nerve·2026
Same author

PGVDA: a pathway-aggregated genetic dosage framework for interpretable disease classification using machine learning.

Briefings in bioinformatics·2026
Same author

First report of <i>Alternaria alternata</i> causing leaf blight on garlic in the Republic of Korea.

Plant disease·2025
Same author

Systematic Surveillance of Fusarium Head Blight in the Southern Region of the Republic of Korea.

Plant disease·2025
Same author

Structural Stability Assessment for Optimal Order Picking in Box-Stacked Storage Logistics.

Sensors (Basel, Switzerland)·2025

Related Experiment Video

Updated: May 25, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.5K

A Semi-Autonomous Telemanipulation Order-Picking Control Based on Estimating Operator Intent for Box-Stacking Storage

Donggyu Min1, Hojin Yoon1, Donghun Lee1

  • 1Mechanical Engineering Department, Soongsil University, Seoul 06978, Republic of Korea.

Sensors (Basel, Switzerland)
|February 26, 2025
PubMed
Summary

This study introduces a semi-autonomous telemanipulation method for logistics order picking. It improves accuracy by estimating operator intent through manipulator motion, reducing fatigue and enhancing efficiency in warehouse automation.

Keywords:
logistics warehouse environmentoperator intent estimationsemi-autonomous control methodsuction-based telemanipulation order picking

More Related Videos

Investigating Motor Skill Learning Processes with a Robotic Manipulandum
07:52

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

8.6K
A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.4K

Related Experiment Videos

Last Updated: May 25, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.5K
Investigating Motor Skill Learning Processes with a Robotic Manipulandum
07:52

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

8.6K
A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.4K

Area of Science:

  • Robotics
  • Human-Robot Interaction
  • Logistics Automation

Background:

  • Teleoperation enhances logistics order picking but faces accuracy issues with immersive human-robot interfaces (HRI) like head-mounted displays (HMDs) due to limited fields of view.
  • Current HRI methods can decrease task accuracy in complex warehouse environments.

Purpose of the Study:

  • To develop a semi-autonomous telemanipulation control method for order picking that enhances accuracy and reduces operator fatigue.
  • To improve human-robot collaboration in logistics by accurately estimating operator intent.

Main Methods:

  • Proposed a two-stage operator intent estimation method using intersection points between the end-effector and target logistics planes.
  • Utilized camera vision for object identification, Gaussian distribution modeling for probability density function (PDF) of target objects, and Bayesian probability filtering.
  • Implemented a control switching mechanism between autonomous and manual controllers based on predefined conditions.

Main Results:

  • The operator intent estimation method correctly identified the target for 74.6% of the task duration.
  • The semi-autonomous control successfully transferred control to the autonomous system within 32.2% of the total task duration.
  • Operator intent was inferred solely from manipulator motion, reducing operator fatigue.

Conclusions:

  • The proposed method offers a significant improvement in teleoperation accuracy for logistics order picking.
  • This approach has broad applicability in teleoperation systems, boosting operational efficiency irrespective of operator skill.
  • The semi-autonomous system reduces operator fatigue and enhances overall warehouse automation performance.