ArticleSensors (Basel, Switzerland)2020
Grip Stabilization through Independent Finger Tactile Feedback Control.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Human-like Dexterous Grasping Through Reinforcement Learning and Multimodal Perception.Biomimetics (Basel, Switzerland) · 2025Article
- Research on Convex Fiber Grating Tactile Sliding Sensor Based on Mechanical Fingers.Sensors (Basel, Switzerland) · 2024Article
- Pressure-Insensitive Epidermal Thickness of Fingertip Skin for Optical Image Encryption.Sensors (Basel, Switzerland) · 2024Article
- Dynamic Focusing (DF) Cone-Based Omnidirectional Fingertip Pressure Sensor with High Sensitivity in a Wide Pressure Range.Sensors (Basel, Switzerland) · 2023Article
- Design and Experimental Research of Robot Finger Sliding Tactile Sensor Based on FBG.Sensors (Basel, Switzerland) · 2022Article
- GradTac: Spatio-Temporal Gradient Based Tactile Sensing.Frontiers in robotics and AI · 2022Article
- Neurophysiology of slip sensation and grip reaction: insights for hand prosthesis control of slippage.Journal of neurophysiology · 2021Review
- Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition.Sensors (Basel, Switzerland) · 2021Article
- Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks.Frontiers in robotics and AI · 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
Grip force control during robotic in-hand manipulation is usually modeled as a monolithic task, where complex controllers consider the placement of all fingers and the contact states between each finger and the gripped object in order to compute the necessary forces to be applied by each finger. Such approaches normally rely on object and contact models and do not generalize well to novel manipulation tasks. Here, we propose a modular grip stabilization method based on a proposition that explains how humans achieve grasp stability. In this biomimetic approach, independent tactile grip stabilization controllers ensure that slip does not occur locally at the engaged robot fingers. Local slip is predicted from the tactile signals of each fingertip sensor i.e., BioTac and BioTac SP by Syntouch. We show that stable grasps emerge without any form of central communication when such independent controllers are engaged in the control of multi-digit robotic hands. The resulting grasps are resistant to external perturbations while ensuring stable grips on a wide variety of objects.
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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.