ReviewSensors (Basel, Switzerland)2021
Human-Robot Perception in Industrial Environments: A Survey.
Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed, 150 citations in OpenAlex.
- Real-Time Terrain Recognition for Quadruped Robots Using Proprioceptive Sensors and Temporal Convolutional Networks.Sensors (Basel, Switzerland) · 2026Article
- From complexity to commercial readiness: industry insights on bridging gaps in human-robot interaction and social robot navigation.Frontiers in robotics and AI · 2025Article
- Multimodal perception-driven decision-making for human-robot interaction: a survey.Frontiers in robotics and AI · 2025Review
- Construction Method of a Digital-Twin Simulation System for SCARA Robots Based on Modular Communication.Sensors (Basel, Switzerland) · 2024Article
- A new CNN-BASED object detection system for autonomous mobile robots based on real-world vehicle datasets.Heliyon · 2024Article
- RobotSDF: Implicit Morphology Modeling for the Robotic Arm.Sensors (Basel, Switzerland) · 2024Article
- Reinforcement Learning with Task Decomposition and Task-Specific Reward System for Automation of High-Level Tasks.Biomimetics (Basel, Switzerland) · 2024Article
- On the Evaluation of Diverse Vision Systems towards Detecting Human Pose in Collaborative Robot Applications.Sensors (Basel, Switzerland) · 2024Article
- A scoping review of gaze and eye tracking-based control methods for assistive robotic arms.Frontiers in robotics and AI · 2024Article
- Mobile Manipulators in Industry 4.0: A Review of Developments for Industrial Applications.Sensors (Basel, Switzerland) · 2023Review
- Domain Adaptation with Contrastive Simultaneous Multi-Loss Training for Hand Gesture Recognition.Sensors (Basel, Switzerland) · 2023Article
- Deep Learning Framework for Controlling Work Sequence in Collaborative Human-Robot Assembly Processes.Sensors (Basel, Switzerland) · 2023Article
- Efficient human 3D localization and free space segmentation for human-aware mobile robots in warehouse facilities.Frontiers in robotics and AI · 2023Article
- Application of Smoothing Spline in Determining the Unmanned Ground Vehicles Route Based on Ultra-Wideband Distance Measurements.Sensors (Basel, Switzerland) · 2022Article
- Development of an Integrated Virtual Reality System with Wearable Sensors for Ergonomic Evaluation of Human-Robot Cooperative Workplaces.Sensors (Basel, Switzerland) · 2022Article
- My Caregiver the Cobot: Comparing Visualization Techniques to Effectively Communicate Cobot Perception to People with Physical Impairments.Sensors (Basel, Switzerland) · 2022Article
- Digital Twin-Driven Human Robot Collaboration Using a Digital Human.Sensors (Basel, Switzerland) · 2021Article
- A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction.Sensors (Basel, Switzerland) · 2021Article
- Evaluation of the Path-Tracking Accuracy of a Three-Wheeled Omnidirectional Mobile Robot Designed as a Personal Assistant.Sensors (Basel, Switzerland) · 2021Article
- Intuitive Spatial Tactile Feedback for Better Awareness about Robot Trajectory during Human-Robot Collaboration.Sensors (Basel, Switzerland) · 2021Article
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 at 2 institutions in 1 country.
Funding
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.
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.