Hand Posture Subspaces for Dexterous Robotic Grasping

By Matei T. Ciocarlie, Peter K. Allen. 2009

457 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Control and Systems Engineering, Human-Computer Interaction

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Citations in the corpus

LILA: Language-Informed Latent Actions (2021, methodology): “We build LILA within a shared autonomy framework [2, 16], applied to assistive teleoperation [17, 18].”
Data-Driven Grasp Synthesis—A Survey (2013, methodology): “Also Goldfeder and Allen [89] built their knowledge base only from synthetic data on which grasps are generated using the previously discussed Eigengrasp planner [44].”
Grasping unknown objects using an Early Cognitive Vision system for general scene understanding (2011, methodology): “A dimensionality reduction of the configuration space of the hand using so-called eigengrasps has been proposed in [13].”
Automated Construction of Robotic Manipulation Programs (2010, background): “Even if the preshape is held constant, efficiently exploring an 8DOF space is very difficult [Ciocarlie and Allen (2009)].”
Cloud-based robot grasping with the google object recognition engine (2013, background): “Each match is a stored image (from training) with its corresponding label and a confidence measure between 0 and 1.”
Learning latent actions to control assistive robots (2021, unknown): “Prior work has tried to prune away unnecessary control axes in a data-driven fashion through Principal Component Analysis [13,4, 33].”
Learning task-oriented grasping for tool manipulation from simulated self-supervision (2018, background): “, 2003), simplifying the search of grasps in a subspace of reduced dimensionality (Ciocarlie and Allen, 2009), and leveraging a dataset of objects with known grasps to speed up grasp selection for novel objects (Goldfeder et al.”
Generalization of human grasping for multi-fingered robot hands (2012, methodology): “Following this idea, various researchers have used dimensionality reduction techniques to find finger synergies in recorded human grasps [4], [8].”
Shared Autonomy with Learned Latent Actions (2020, methodology): “Previous works have leveraged latent actions for intuitive low-DoF control of assistive robots, where latent actions enable users to express their desired high-DoF motion [19, 5, 3].”
Pose error robust grasping from contact wrench space metrics (2012, methodology): “The grasps discussed in this paper were produced using the Eigengrasp planner presented by Ciocarlie et al.[19].”
Grasp'D: Differentiable Contact-rich Grasp Synthesis for Multi-fingered Hands (2022, unknown): “We address this with a problem relaxation inspired by Contact-Invariant Optimization [64, 65] (see Section 3.4).”
Learning User-Preferred Mappings for Intuitive Robot Control (2020, background): “Many research efforts are devoted to tackle this problem [11]–[13].”
Dual arm manipulation - A survey (2012, background): “New perspectives in the grasp synthesis arise by considering the concept of " postural synergies " or " hand configuration subspace " implying underactuated system of cooperative manipulators [57] [58].”