2021 IEEE 4th International Conference on Soft Robotics (RoboSoft) 2021
DOI: 10.1109/robosoft51838.2021.9479216
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Topological Study on the Design of Soft Strain Sensors for Simultaneous Multi-point Contact Localization

Abstract: Soft strain sensors have been widely used for the development of electronic skins both for robotic and wearable applications. To sense contact location on a wide surface, the standard methodology consists of square grids of strain fibers that are able to detect single contact points but fail to detect multiple ones simultaneously. To avoid such a problem, state-ofthe-art technologies implement sequential sampling that isolates each sensing node, but at the cost of a lower sampling rate. This theoretical study … Show more

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Cited by 7 publications
(4 citation statements)
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“…In order to classify the user's motion intention, hollow cavities are introduced within the soft interface and their internal pressure is recorded: the geometry and position of the cavities will perform morphological computation on the interaction forces caused by palpation and the structural embodied intelligence of the device intrinsically encodes the contact information [36]. Geometry-and location-based morphological computation is an important tool often exploited while working with soft materials to perform accurate contact classification while maintaining a completely soft structure [37], [38], and has already been studied in relation to contact detection [39], [40] and palpation [41]. This paper will showcase 3 different HMI designs and quantify the performance of every design's embodied intelligence using the Silhouette score to investigate the feasibility of encoding a 5 DoF motion from the recorded pressure signal.…”
Section: Introductionmentioning
confidence: 99%
“…In order to classify the user's motion intention, hollow cavities are introduced within the soft interface and their internal pressure is recorded: the geometry and position of the cavities will perform morphological computation on the interaction forces caused by palpation and the structural embodied intelligence of the device intrinsically encodes the contact information [36]. Geometry-and location-based morphological computation is an important tool often exploited while working with soft materials to perform accurate contact classification while maintaining a completely soft structure [37], [38], and has already been studied in relation to contact detection [39], [40] and palpation [41]. This paper will showcase 3 different HMI designs and quantify the performance of every design's embodied intelligence using the Silhouette score to investigate the feasibility of encoding a 5 DoF motion from the recorded pressure signal.…”
Section: Introductionmentioning
confidence: 99%
“…Previous studies in the field of filter-based tactile sensing have focused on the effect of the filter’s morphology on the structure and quality of the recorded data, investigating the information gain’s maximization ( Thuruthel et al, 2020 ), the amplification of the sensor’s sensitivity ( Fend et al, 2004 ), task-specific optimization ( Qi and Hirai, 2019 ), and the relationship between redundancy and localization error ( Costi et al, 2021b ). Moreover, researchers have deeply studied the relationship between the morphology of the sensor and the action for perception ( Huang et al, 2019 ; Scimeca et al, 2020b , 2021 ).…”
Section: Introductionmentioning
confidence: 99%
“…Previously, researchers in this field have focused on the effect of different morphology designs, investigating the maximization of the information gain [7], the role of redundancy [8], sensitivity amplification [9], and task-specific optimization [10]. Moreover, there has been a considerable amount of studies on the relationship between the morphology of the Manuscript received: October 11, 2021; Revised: January 11, 2022; Accepted: February 28, 2022. This paper was recommended for publication by Editor Cecilia Laschi upon evaluation of the Associate Editor and Reviewers' comments.…”
Section: Introductionmentioning
confidence: 99%