Slip detection and control using tactile and force sensors

Melchiorri, Claudio

doi:10.1109/3516.868914

Cited by 163 publications

(89 citation statements)

References 17 publications

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“…The review addressed the basic closure properties of grasps, force and form closure, which describe the equilibrium conditions of an object grasped by a robotic hand by assuming frictional and frictionless point contacts respectively. Given that friction forces play a central role in robotic grasping, some of the works reported in the literature have focused on studying their properties [5], [10]. These studies cover not only the translational Coulomb friction, but also the rotational friction.…”

Section: Related Workmentioning

confidence: 99%

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Predicting slippage and learning manipulation affordances through Gaussian Process regression

Viña

Bekiroglu

Smith

et al. 2013

2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids)

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Abstract-Object grasping is commonly followed by some form of object manipulation -either when using the grasped object as a tool or actively changing its position in the hand through in-hand manipulation to afford further interaction. In this process, slippage may occur due to inappropriate contact forces, various types of noise and/or due to the unexpected interaction or collision with the environment.In this paper, we study the problem of identifying continuous bounds on the forces and torques that can be applied on a grasped object before slippage occurs. We model the problem as kinesthetic rather than cutaneous learning given that the measurements originate from a wrist mounted force-torque sensor. Given the continuous output, this regression problem is solved using a Gaussian Process approach.We demonstrate a dual armed humanoid robot that can autonomously learn force and torque bounds and use these to execute actions on objects such as sliding and pushing. We show that the model can be used not only for the detection of maximum allowable forces and torques but also for potentially identifying what types of tasks, denoted as manipulation affordances, a specific grasp configuration allows. The latter can then be used to either avoid specific motions or as a simple step of achieving in-hand manipulation of objects through interaction with the environment.

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Section: Related Workmentioning

confidence: 99%

“…These studies cover not only the translational Coulomb friction, but also the rotational friction. Moreover, by combining different sensor modalities (tactile and force-torque) it is shown in [5] that it is possible to detect and control both translational and rotational slippage.…”

Section: Related Workmentioning

confidence: 99%

Predicting slippage and learning manipulation affordances through Gaussian Process regression

Viña

Bekiroglu

Smith

et al. 2013

2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids)

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“…The FSR varies its resistance depending on how much pressure is applied to the sensing area. The greater the force, the lower the resistance [3].…”

Section: A Tactile Slip Sensormentioning

confidence: 99%

“…The two front wheels are driven by the two 12V BLDC motor [2]. Tactile slip sensors (FSR) made from Polyvinylidene difluoride (PVDF) materials attached to the robot's handle to detect the force / pressure which conveys users intended motion speed and direction and sends the signal to the ATMega 16 micro controller [3].…”

Section: Elderly Assistant and Walking Assistant Robot Descriptionmentioning

confidence: 99%

PID Control of Elderly Assistant and Walking Assistant Robot

Osivue

Zhang

et al. 2017

Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

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Abstract-In this paper, a PID controller is applied to control the speed and direction of an elderly-assistant and walking-assistant robot (EWR) by controlling the speed and direction of two 12V brushless DC (BLDC) motor driving two front hub wheel of the EWR. C code for the PID controller run on ATMega16 microcontroller. The parameter of a standard PID controller for the BLDC motor speed and direction control system under the investigation is tuned and fixed throughout the control. The result of the experiment on the real plant demonstrates that the PID controller is a good choice to suppress the oscillation due to the systems and sensors nonlinearity.

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“…Several papers deal with the shape reconstruction from tactile images [17], [18], [19]. Zhang and Chen use tactile sensing to control a robot trajectory [20], while Melchiori detects the slippage of objects via tactile sensing [21]. Once again, every new algorithm working on tactile data has to prove its performance in an experiment.…”

Section: A Related Workmentioning

confidence: 99%

Acquisition and Application of a Tactile Database

Schöpfer

Ritter

Heidemann

2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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Abstract-We present a database of 2D pressure profile timeseries as a testbed for tactile object and surface recognition. The tactile database captures the surfaces of household and toy objects by moving a 2D pressure sensor mounted to an industrial robot arm around the objects using real-time trajectory calculation. Thus, it represents different "views" of the objects in a similar way as the well known Columbia Object Image Library (COIL) captures different views of an object by a camera. As a first application, objects in the database are classified using a neural network architecture.

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Slip detection and control using tactile and force sensors

Cited by 163 publications

References 17 publications

Predicting slippage and learning manipulation affordances through Gaussian Process regression

Predicting slippage and learning manipulation affordances through Gaussian Process regression

PID Control of Elderly Assistant and Walking Assistant Robot

Acquisition and Application of a Tactile Database

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