Methods and Technologies for the Implementation of Large-Scale Robot Tactile Sensors

Schmitz, Alexander; Maiolino, Perla; Maggiali, Marco; Natale, Lorenzo; Cannata, Giorgio; Metta, Giorgio

doi:10.1109/tro.2011.2132930

Cited by 363 publications

(254 citation statements)

References 24 publications

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“…The tactile sensor has a rounded shape that resembles a human fingertip [16], with dimensions 14.5 mm long by 13 mm wide. It consists of an inner support wrapped with a flexible printed circuit board containing 12 conductive patches for the touch sensor 'taxels', about 4 mm apart.…”

Section: Tactile Data Collectionmentioning

confidence: 99%

See 1 more Smart Citation

Active Bayesian Perception for Simultaneous Object Localization and Identification

Lepora¹,

Martinez-Hernandez²,

Prescott³

2013

Robotics: Science and Systems IX

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Abstract-In this paper, we propose that active Bayesian perception has a general role for Simultaneous Object Localization and IDentification (SOLID), or deciding where and what. We test this claim using a biomimetic fingertip to perceive object identity via surface shape at uncertain contact locations. Our method for active Bayesian perception combines decision making by threshold crossing of the posterior belief with a sensorimotor loop that actively controls sensor location based on those beliefs. Our findings include: (i) active perception with a fixation control strategy gives an order-of-magnitude improvement in acuity over passive perception without sensorimotor feedback; (ii) perceptual acuity improves as the active control requires less belief to make a relocation decision; and (iii) relocation noise further improves acuity. The best method has aspects that resemble animal perception, supporting wide applicability of these findings.

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Section: Tactile Data Collectionmentioning

confidence: 99%

“…This is coated with non-conductive foam and conductive silicone layers, together comprising a capacitive touch sensor that detects pressure via compression. Data were collected at 8-bit resolution and 50 cycles/sec then high-pass filtered and normalized [16].…”

Section: Tactile Data Collectionmentioning

confidence: 99%

Active Bayesian Perception for Simultaneous Object Localization and Identification

Lepora¹,

Martinez-Hernandez²,

Prescott³

2013

Robotics: Science and Systems IX

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“…Furthermore, the implementation of the proposed sensorimotor control strategies indicates how the weight 35 and reliability of the information improve the perceptual accuracy and speed during the exploration task. The findings 36 of this investigation provide new robust and accurate computational methods to exploit the advances and integration 37 of tactile sensing technology in robotics.…”

mentioning

confidence: 95%

“…For this work, we used a biomimetic fingertip sensor that is part of the tactile sensory system of the iCub humanoid 91 robot [36]. This tactile sensory system provides the iCub humanoid robot with capabilities to interact with its 92 environment [37].…”

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confidence: 99%

Active sensorimotor control for tactile exploration

Martinez-Hernandez

Dodd

Evans

et al. 2017

Robotics and Autonomous Systems

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Please cite this article as: U. Martinez-Hernandez, et al., Active sensorimotor control for tactile exploration, Robotics and Autonomous Systems (2016), http://dx.doi.org/10. 1016/j.robot.2016.09.014 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Active sensorimotor control for tactile exploration AbstractIn this paper, we present a novel and robust Bayesian approach for autonomous active exploration of unknown objects using tactile perception and sensorimotor control. Despite recent advances in tactile sensing, robust active exploration remains a challenging problem, which is a major hurdle to the practical deployment of tactile sensors in robots.Our proposed approach is based on a Bayesian perception method that actively controls the sensor with local small repositioning movements to reduce perception uncertainty, followed by explorative movements based on the outcome of each perceptual decision making step. Two sensorimotor control strategies are proposed for improving the accuracy and speed of the active exploration that weight the evidence from previous exploratory steps through either a weighted prior or weighted posterior. The methods are validated both off-line and in real-time on a contour following exploratoryprocedure. Results clearly demonstrate improvements in both accuracy and exploration time when using the proposed active methods compared to passive perception. Our work demonstrates that active perception has the potential to enable robots to perform robust autonomous tactile exploration in natural environments.

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“…Then, the robotic hand makes a decision once the belief threshold about the object being explored is exceeded. This method has been tested for object shape extraction [5], [6] and simultaneous object localisation and identification [7], [8] using the fingertip sensors from the iCub humanoid robot [18].…”

Section: Bayesian Estimatormentioning

confidence: 99%

Active Control for Object Perception and Exploration with a Robotic Hand

Martinez-Hernandez

Lepora

Prescott

2015

Lecture Notes in Computer Science

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Abstract. We present an investigation on active control for intelligent object exploration using touch with a robotic hand. First, uncertainty from the exploration is reduced by a probabilistic method based on the accumulation of evidence through the interaction with an object of interest. Second, an intrinsic motivation approach allows the robot hand to perform intelligent active control of movements to explore interesting locations of the object. Passive and active perception and exploration were implemented in simulated and real environments to compare their benefits in accuracy and reaction time. The experiments for validation of the proposed method were performed with an object recognition task, using a robotic platform composed by a three-fingered robotic hand and a robot table. The results demonstrate that our method permits to the robotic hand to achieve high accuracy for object recognition with low impact on the reaction time required to perform the task. These benefits make the proposed method suitable for perception and exploration in autonomous robotics.

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Methods and Technologies for the Implementation of Large-Scale Robot Tactile Sensors

Cited by 363 publications

References 24 publications

Active Bayesian Perception for Simultaneous Object Localization and Identification

Active Bayesian Perception for Simultaneous Object Localization and Identification

Active sensorimotor control for tactile exploration

Active Control for Object Perception and Exploration with a Robotic Hand

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