ReviewSensors (Basel, Switzerland)2023
Mobile Manipulators in Industry 4.0: A Review of Developments for Industrial Applications.
Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- Adaptive constraint-following control for maintenance robotic manipulator with uncertainties.Scientific reports · 2026Article
- A Complete Grocery Pick-and-Pack Application Using a Computationally Lightweight Vision-Based Mobile Manipulator.Sensors (Basel, Switzerland) · 2026Article
- Integrating self-attention and LSTM into TD3 for robust mobile robot navigation in dynamic environments.Scientific reports · 2026Article
- A Mechanical Structure Design and Simulation-Based Validation of a Novel Compact and Low-Cost 3-DOF Robotic Arm.Sensors (Basel, Switzerland) · 2025Article
- An End-to-End Computationally Lightweight Vision-Based Grasping System for Grocery Items.Sensors (Basel, Switzerland) · 2025Article
- Improved Adaptive Sliding Mode Control Using Quasi-Convex Functions and Neural Network-Assisted Time-Delay Estimation for Robotic Manipulators.Sensors (Basel, Switzerland) · 2025Article
- HEPSO-SMC: a sliding mode controller optimized by hybrid enhanced particle swarm algorithm for manipulators.Scientific reports · 2025Article
- Dynamic Cooperative Communications with Mutual Information Accumulation for Mobile Robots in Industrial Internet of Things.Sensors (Basel, Switzerland) · 2024Article
- Fast 50 Hz Updated Static Infrared Positioning System Based on Triangulation Method.Sensors (Basel, Switzerland) · 2024Article
- Reliable and robust robotic handling of microplates via computer vision and touch feedback.Frontiers in robotics and AI · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the realm of Industry 4.0, diverse technologies such as AI, Cyber-Physical Systems, IoT, and advanced sensors converge to shape smarter future factories. Mobile manipulators (MMs) are pivotal, fostering flexibility, adaptability, and collaboration in industrial processes. On one hand, MMs offer a remarkable level of flexibility, adaptability, and collaboration in industrial processes, facilitating swift production line changes and efficiency enhancements. On the other hand, their integration into real manufacturing environments requires meticulous considerations, such as safety, human-robot interaction, and cybersecurity. This article delves into MMs' essential role in achieving Industry 4.0's automation and adaptability by integrating mobility with manipulation capabilities. The study reviews MMs' industrial applications and integration into manufacturing systems. The most observed applications are logistics (49%) and manufacturing (33%). As Industry 4.0 advances, the paper emphasizes updating and aligning MMs with the smart factory concept by networks of sensors and the real-time analysis of them, especially for an enhanced human-robot interaction. Another objective is categorizing considerations for MMs' utilization in Industry 4.0-aligned manufacturing. This review methodically covers a wide range of considerations and evaluates existing solutions. It shows a more comprehensive approach to understanding MMs in Industry 4.0 than previous works. Key focus areas encompass perception, data analysis, connectivity, human-robot interaction, safety, virtualization, and cybersecurity. By bringing together different aspects, this research emphasizes a more integrated view of the role and challenges of MMs in the Industry 4.0 paradigm and provides insights into aspects often overlooked. A detailed and synthetic analysis of existing knowledge was performed, and insights into their future path in Industry 4.0 environments were provided as part of the contributions of this paper. The article also appraises initiatives in these domains, along with a succinct technology readiness analysis. To sum up, this study highlights MMs' pivotal role in Industry 4.0, encompassing their influence on adaptability, automation, and efficiency.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.