Localization Based Grasping for Robotic Grippers
DOI:
https://doi.org/10.54097/948twa81Keywords:
Robotic grippers, grasping methods, sensors, localization.Abstract
To meet the demands of grasping in complex environments, robotic grippers are moving from traditional open-loop control to perception-based closed-loop localization for grasping. Open-loop control lacks real-time feedback and struggles with the uncertainty of unstructured settings. In contrast, closed-loop grasping with multimodal sensing such as vision and touch adapts the strategy online and increases success rates. This paper reviews three categories of grippers and their development, namely industrial, medical, and soft. Industrial grippers provide high stiffness, high payload capacity, and high precision. They meet heavy-load and high-accuracy requirements in production and use vision and control algorithms to raise grasp success. Medical grippers emphasize compliance and micro-manipulation so that surgery meets strict requirements on fine control and safety. They combine force sensing and vision to ensure safe and stable operation. Soft grippers use compliant structures and under-actuated designs to perform enveloping grasps on irregular objects that improves tolerance to error and adaption to shape. Finally, the paper summarizes the value and challenges of fusing vision, tactile sensing, and force sensing with localization strategies in closed-loop grasp control.
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