Robot Grasp Synthesis Algorithms: A Survey

By K. Shimoga. 1996

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Citations in the corpus

Deep learning for detecting robotic grasps (2013, background): “[53], Bicchi and Kumar [2] and Shimoga [58].”
The Curious Robot: Learning Visual Representations via Physical Interactions (2016, background): “ comprehensive literature review of this area can be found in [15,16]. Most work in this area has focused on using analytical methods and 3D reasoning for predicting grasp locations and congurations [17,18,19,20] but assume the availability of complete physical knowledge of the objects. However, rec”
Data-Driven Grasp Synthesis—A Survey (2013, methodology): “Following Shi-moga [2], analytic refers to methods that construct force-closure grasps with a multi-ﬁngered robotic hand that are dexterous , in equilibrium , stable and exhibit a certain dynamic behaviour .”
Learning to push by grasping: Using multiple tasks for effective learning (2016, background): “Analytical frameworks such as [1], [2], [3] focus on defining (c) via mathematical framework.”
Soft magnetic skin for super-resolution tactile sensing with force self-decoupling (2021, background): “7 N) until Fx/Fz drops into the safe area inside the friction cone to preclude slippage (38).”
Dual arm manipulation - A survey (2012, background): “The choice of optimal grasp synthesis and its evaluation, as well the force distribution problem for object grasping [52] [153] [159], are of fundamental importance and has been extensively explored in recent publications [53] [54] [55] [56].”
Development of a high-speed multifingered hand system and its application to catching (2003, background): “There has been considerable theoretical work on a multifingered hand addressed to: grasp stability, force analysis, and dynamic control [4].”
Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach (2018, background): “Robotic grasping has been investigated for decades, yielding a multitude of different techniques [2, 3, 27, 29].”
Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network (2019, methodology): “Initially for obtaining a stable grasp, the mechanics and contact kinematics of the end effector in contact with the object were studied and the grasp analysis was performed as seen from the survey by [9], [10].”
Learning grasp affordance densities (2011, background): “The most popular 3D model for grasping is the 3D mesh, which allows for studying contact forces, and for finding a force-closure optimal grasp therefrom [1, 17, 21, 30].”
AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domains (2022, methodology): “Early methods would assume full 2D or 3D knowledge of the objects [12], [13], or approximate the objects into a set of primitive shapes [14], [15].”
Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding (2010, methodology): “We refer the reader to existing surveys [4], [27] for a more comprehensive literature review on the broad domain of grasping research.”
An overview of 3D object grasp synthesis algorithms (2012, background): “Robot grasp synthesis algorithms have been reviewed in [63], but since then an important progress has been made toward applying learning techniques to the grasping problem.”
Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight (2019, methodology): “ing of the selected tool [31, 40, 5, 2, 14], and using the grasped tool through planning [29] or policy learning [14].”
Dynamic object manipulation using a virtual frame by a triple soft-fingered robotic hand (2010, background): “However, it is hard to realize to do because many difficulties have still now been unsolved [1] [2] [3].”
Real-World Multiobject, Multigrasp Detection (2018, background): “Altogether, the review papers [5]–[8] provide a good context for the overall field.”
Learning visual representations for perception-action systems (2011, methodology): “Then, grasp contact points can be computed using established theory (Shimoga 1996).”