ArticleSensors (Basel, Switzerland)2023
Spatial Calibration of Humanoid Robot Flexible Tactile Skin for Human-Robot Interaction.
Article 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 2 papers.
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The trial behind it
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Who cites it
2 citing papers in PubMed.
- Recent Advances in Self-Powered Tactile Sensing for Wearable Electronics.Materials (Basel, Switzerland) · 2024Review
- Flexible Strain Sensors Based on Bionic Parallel Vein-like Structures for Human Motion Monitoring.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Recent developments in robotics have enabled humanoid robots to be used in tasks where they have to physically interact with humans, including robot-supported caregiving. This interaction-referred to as physical human-robot interaction (pHRI)-requires physical contact between the robot and the human body; one way to improve this is to use efficient sensing methods for the physical contact. In this paper, we use a flexible tactile sensing array and integrate it as a tactile skin for the humanoid robot HRP-4C. As the sensor can take any shape due to its flexible property, a particular focus is given on its spatial calibration, i.e., the determination of the locations of the sensor cells and their normals when attached to the robot. For this purpose, a novel method of spatial calibration using B-spline surfaces has been developed. We demonstrate with two methods that this calibration method gives a good approximation of the sensor position and show that our flexible tactile sensor can be fully integrated on a robot and used as input for robot control tasks. These contributions are a first step toward the use of flexible tactile sensors in pHRI applications.
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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.