Abstract
One of the crucial actions to be performed during a grasping task is to avoid slippage. The human hand can rapidly correct applied forces and prevent a grasped object from falling, thanks to its advanced tactile sensing. The same capability is hard to reproduce in artificial systems, such as robotic or prosthetic hands, where sensory motor coordination for force and slippage control is very limited. In this paper, a novel algorithm for slippage detection is presented. Based on fast, easy-to-perform processing, the proposed algorithm generates an ON/OFF signal relating to the presence/absence of slippage. The method can be applied either on the raw output of a force sensor or to its calibrated force signal, and yields comparable results if applied to both normal or tangential components. A biomimetic fingertip that integrates piezoresistive MEMS sensors was employed for evaluating the method performance. Each sensor had four units, thus providing 16 mono-axial signals for the analysis. A mechatronic platform was used to produce relative movement between the finger and the test surfaces (tactile stimuli). Three surfaces with submillimetric periods were adopted for the method evaluation, and 10 experimental trials were performed per each surface. Results are illustrated in terms of slippage events detection and of latency between the slippage itself and its onset.
Highlights
Tactile sensing is fundamental for enhancing performance of robotic systems in unstructured environments
While the robotic end effector performs an action or handles an object, unpredictable events might occur, which hinder the success of the action; the availability of control strategies relying on tactile sensory feedback could greatly increase robot performance when facing such a situation
Input, it should be noticed that the algorithm output somehow depends from the applied pressure and is followed by the rectification and exponentiation of the signal, which is in level, i.e., the higher the exerted pressure on the sensor is, the higher the amplitude of the signal turn followed by an enveloping phase
Summary
Tactile sensing is fundamental for enhancing performance of robotic systems in unstructured environments. A new method [23] for the detection of slippage events is proposed; it provides an ON/OFF slip information thanks to online processing of a force sensor output. Simple operations such as digital filtering, rectification and envelope of the input signal are cascaded in order to generate the ON/OFF slip signal. It is possible to convert such an input into a force signal by using calibration matrices [26]; the voltage signal contains all the necessary information for applying the proposed slippage detection algorithm This approach is highly convenient for online applications, e.g., a robotic hand control system.
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