Angled sensor configuration capable of measuring tri-axial forces for pHRI

Reeks, Christian; Carmichael, Marc G.; Liu, Dikai; Waldron, Kenneth J.

doi:10.1109/icra.2016.7487475

Cited by 7 publications

(4 citation statements)

References 18 publications

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“…The grasp detection mechanism that uses the capacitive touch buttons does not allow closed loop control on the haptic feedback and modulating the output based on the detected grasp does not guarantee precise haptic output, allowing the learners to release the robots and follow their motion which is due to the motor outputs intended for haptic feedback. To mitigate these problems, we are investigating force/torque sensors to be installed on the outer shell of the robot; [31] is a promising candidate for this purpose. In addition, the user study was conducted with a limited number of participants, and more could allow us to obtain clearer results on learning gains.…”

Section: Discussionmentioning

confidence: 99%

Windfield

Özgür

Johal

Mondada

et al. 2017

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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This article presents a learning activity and its user study involving the Cellulo platform, a novel versatile robotic tool designed for education. In order to show the potential of Cellulo in the classroom as part of standard curricular activities, we designed a learning activity called Windfield that aims to teach the atmospheric formation mechanism of wind to early middle school children. The activity involves a didactic sequence, introducing the Cellulo robots as hot air balloons and enabling children to feel the wind force through haptic feedback. We present a user study, designed in the form of a real hour-long lesson, conducted with 24 children in 8 groups who had no prior knowledge in the subject. Collaborative metrics within groups and individual performances about the learning of key concepts were measured with only the hardware and software integrated in the platform in a completely automated manner. The results show that almost all participants showed learning of symmetric aspects of wind formation while about half showed learning of asymmetric vectorial aspects that are more complex.

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Section: Discussionmentioning

confidence: 99%

Windfield

Özgür

Johal

Mondada

et al. 2017

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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“…Their accuracy is significantly impacted by the orientation of the sensor. In [20], it was found that placing the sensor at a 45°angle with respect to the contact pad yields the best results. A minimal RMSE of 1.74 N was found for the normal force.…”

Section: Related Work a Tactile Sensorsmentioning

confidence: 99%

A Soft Barometric Tactile Sensor to Simultaneously Localize Contact and Estimate Normal Force With Validation to Detect Slip in a Robotic Gripper

Clercq

Sianov

Crevecoeur

2022

IEEE Robot. Autom. Lett.

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Soft tactile sensing technologies provide the potential to endow a sense of touch to robots for grasping and manipulating objects. During the execution of such tasks, having accurate knowledge on the contact location and quantitative forces in broad exerted force ranges is key. For industrial adoption such sensor needs to be low-cost, robust with limited or no calibration procedures and easy to manufacture. In this work we present a microelectromechanical (MEMS) based barometric sensor array covered with an elastomer layer, with the sensor signals being interpreted in real-time on the basis of a parameterized Gaussian type of distribution. The contact location is determined by finding in real-time the corresponding parameters of the Gaussian distribution that on its turn is used for normal contact force estimation. Results show accuracies in terms of localization of 0.5 mm and normal force errors of 10 % in force ranges up to 25 N and 15 % in high force ranges of 25 -50 N. The proposed soft tactile sensor has furthermore been validated to provide the ability to detect slip when gripping various objects.

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“…We use Takktile from Right Hand Robotics [6] as the sensing elements in our tactile dome. While these sensors are mainly designed to measure normal forces, Reeks et al [7] has shown that positioning these sensors at an angle can produce meaningful signals to measure shear forces. In contrast, our work focuses on contact localization over a three dimensional surface and does not provide force measurements.…”

Section: Related Workmentioning

confidence: 99%

Data-driven Super-resolution on a Tactile Dome

Piacenza,

Sherman,

Ciocarlie

2018

Preprint

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While tactile sensor technology has made great strides over the past decades, applications in robotic manipulation are limited by aspects such as blind spots, difficult integration into hands, and low spatial resolution. We present a method for localizing contact with high accuracy over curved, three dimensional surfaces, with a low wire count and reduced integration complexity. To achieve this, we build a volume of soft material embedded with individual off-the-shelf pressure sensors. Using data driven techniques, we map the raw signals from these pressure sensors to known surface locations and indentation depths. Additionally, we show that a finite element model can be used to improve the placement of the pressure sensors inside the volume and to explore the design space in simulation. We validate our approach on physically implemented tactile domes which achieve high contact localization accuracy (1.1mm in the best case) over a large, curved sensing area (1, 300mm 2 hemisphere). We believe this approach can be used to deploy tactile sensing capabilities over three dimensional surfaces such as a robotic finger or palm.

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Angled sensor configuration capable of measuring tri-axial forces for pHRI

Cited by 7 publications

References 18 publications

Windfield

Windfield

A Soft Barometric Tactile Sensor to Simultaneously Localize Contact and Estimate Normal Force With Validation to Detect Slip in a Robotic Gripper

Data-driven Super-resolution on a Tactile Dome

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