ArticleFrontiers in robotics and AI2019
Design Considerations for 3D Printed, Soft, Multimaterial Resistive Sensors for Soft Robotics.
Article in Frontiers in robotics and AI, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 102 citations in OpenAlex.
- Programmable somatosensory soft robots.Npj flexible electronics · 2026Article
- Fabrication of Soft Robotics by Additive Manufacturing: From Materials to Applications.Chemical reviews · 2025Review
- A retrofit sensing strategy for soft fluidic robots.Nature communications · 2024Article
- Sensing in Soft Robotics.ACS nano · 2023Review
- Hybrid Device Fabrication Using Roll-to-Roll Printing for Personal Environmental Monitoring.Polymers · 2023Article
- A review on model-based and model-free approaches to control soft actuators and their potentials in colonoscopy.Frontiers in robotics and AI · 2023Review
- A binder jet 3D printed MXene composite for strain sensing and energy storage application.Nanoscale advances · 2022Article
- Self-Concern Across Scales: A Biologically Inspired Direction for Embodied Artificial Intelligence.Frontiers in neurorobotics · 2022Review
- Review of machine learning methods in soft robotics.PloS one · 2021Review
- Fabrication of a Soft Robotic Gripper With Integrated Strain Sensing Elements Using Multi-Material Additive Manufacturing.Frontiers in robotics and AI · 2021Article
- A Deep Learning Method for Vision Based Force Prediction of a Soft Fin Ray Gripper Using Simulation Data.Frontiers in robotics and AI · 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
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sensor design for soft robots is a challenging problem because of the wide range of design parameters (e.g., geometry, material, actuation type, etc.) critical to their function. While conventional rigid sensors work effectively for soft robotics in specific situations, sensors that are directly integrated into the bodies of soft robots could help improve both their exteroceptive and interoceptive capabilities. To address this challenge, we designed sensors that can be co-fabricated with soft robot bodies using commercial 3D printers, without additional modification. We describe an approach to the design and fabrication of compliant, resistive soft sensors using a Connex3 Objet350 multimaterial printer and investigated an analytical comparison to sensors of similar geometries. The sensors consist of layers of commercial photopolymers with varying conductivities. We characterized the conductivity of TangoPlus, TangoBlackPlus, VeroClear, and Support705 materials under various conditions and demonstrate applications in which we can take advantage of these embedded sensors.
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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.