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High-performing adaptive grasp for a robotic gripper using super twisting sliding mode control

Saber Mahboubi Heydarabad, Ferdinando Milella, Steven Davis, Samia Nefiti-Meziani

发表年份
2017
引用次数
9

摘要

Grasping an object in the presence of unpredictable disturbances and with no previous knowledge of the geometry and mass distribution of it represents a significant challenge in Robotics. Also, grasping an object with sufficient force to prevent slippage, whilst not damaging or deforming the shape of the object proves to be still an intricate challenge despite the existence of a huge body of literature on robotic grasping. This paper addresses this challenge by evaluating the performance of a Super Twisting Sliding Mode Control (STSMC) designed for preventing slippage meanwhile causing minimum deformation to the grasped object. The performance of the STSMC is evaluated against the one of a First Order Sliding Mode Controller (FOSMC). Both controllers use grip force and slip feedback to counteract the slippage. Force and slip detection are provided by low-cost, off-the-shelf sensors. Experimental results presented in this paper, show that, when grasping objects, both controllers can robustly overcome external nonlinear disturbances, along with inaccuracies in the system model, preventing slippage and minimising deformation of objects. However, from these results, we observe that the STSMC not only, as expected, eliminates the major drawback of the FOSMC, which is chattering, but also provides more consistent and robust response in terms of slippage and gripping force.

关键词

SlippageGRASPSlip (aerodynamics)Control theory (sociology)Computer scienceArtificial intelligenceNonlinear systemObject (grammar)Computer visionRobotics

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