ArticleSensors (Basel, Switzerland)2019
Collision Detection and Identification on Robot Manipulators Based on Vibration Analysis.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- A Self-Collision Detection Algorithm of a Dual-Manipulator System Based on GJK and Deep Learning.Sensors (Basel, Switzerland) · 2023Article
- VibroTouch: Active Tactile Sensor for Contact Detection and Force Sensing via Vibrations.Sensors (Basel, Switzerland) · 2022Article
- Collision Localization and Classification on the End-Effector of a Cable-Driven Manipulator Applied to EV Auto-Charging Based on DCNN-SVM.Sensors (Basel, Switzerland) · 2022Article
- Uncertainty-Aware Knowledge Distillation for Collision Identification of Collaborative Robots.Sensors (Basel, Switzerland) · 2021Article
- A Simple Neural Network for Collision Detection of Collaborative Robots.Sensors (Basel, Switzerland) · 2021Article
- Natural Frequencies Identification by FEM Applied to a 2-DOF Planar Robot and Its Validation Using MUSIC Algorithm.Sensors (Basel, Switzerland) · 2021Article
- A Mixed-Perception Approach for Safe Human-Robot Collaboration in Industrial Automation.Sensors (Basel, Switzerland) · 2020Article
- Sensor Signal and Information Processing II.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Robot manipulators should be able to quickly detect collisions to limit damage due to physical contact. Traditional model-based detection methods in robotics are mainly concentrated on the difference between the estimated and actual applied torque. In this paper, a model independent collision detection method is presented, based on the vibration features generated by collisions. Firstly, the natural frequencies and vibration modal features of the manipulator under collisions are extracted with illustrative examples. Then, a peak frequency based method is developed for the estimation of the vibration modal along the manipulator structure. The vibration modal features are utilized for the construction and training of the artificial neural network for the collision detection task. Furthermore, the proposed networks also generate the location and direction information about contact. The experimental results show the validity of the collision detection and identification scheme, and that it can achieve considerable accuracy.
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.