Papers Grasp Generation
“Grasp Generation” 태그가 달린 논문 52편 · 필터 해제
GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training
Grasping is a fundamental robot skill, yet despite significant research advancements, learning-based 6-DOF grasping approaches are still not turnkey and struggle to generalize across different embodiments and in-the-wild…
Grasp GenerationA Unified Transformer-Based Framework with Pretraining For Whole Body Grasping Motion Generation
Accepted in the ICIP 2025 We present a novel transformer-based framework for whole-body grasping that addresses both pose generation and motion infilling, enabling realistic and stable object interactions. Our pipeline c…
Grasp GenerationMotion GenerationExploiting Radiance Fields for Grasp Generation on Novel Synthetic Views
Vision based robot manipulation uses cameras to capture one or more images of a scene containing the objects to be manipulated. Taking multiple images can help if any object is occluded from one viewpoint but more visibl…
Grasp GenerationNovel View SynthesisRobot ManipulationGrasping a Handful: Sequential Multi-Object Dexterous Grasp Generation
We introduce the sequential multi-object robotic grasp sampling algorithm SeqGrasp that can robustly synthesize stable grasps on diverse objects using the robotic hand's partial Degrees of Freedom (DoF). We use SeqGrasp …
Grasp GenerationEvolvingGrasp: Evolutionary Grasp Generation via Efficient Preference Alignment
Dexterous robotic hands often struggle to generalize effectively in complex environments due to the limitations of models trained on low-diversity data. However, the real world presents an inherently unbounded range of s…
Grasp GenerationGAGrasp: Geometric Algebra Diffusion for Dexterous Grasping
We propose GAGrasp, a novel framework for dexterous grasp generation that leverages geometric algebra representations to enforce equivariance to SE(3) transformations. By encoding the SE(3) symmetry constraint directly i…
Grasp GenerationBring Your Own Grasp Generator: Leveraging Robot Grasp Generation for Prosthetic Grasping
One of the most important research challenges in upper-limb prosthetics is enhancing the user-prosthesis communication to closely resemble the experience of a natural limb. As prosthetic devices become more complex, user…
3D geometryGrasp GenerationTask-Oriented 6-DoF Grasp Pose Detection in Clutters
In general, humans would grasp an object differently for different tasks, e.g., "grasping the handle of a knife to cut" vs. "grasping the blade to hand over". In the field of robotic grasp pose detection research, some e…
Grasp GenerationControllable Hand Grasp Generation for HOI and Efficient Evaluation Methods
Controllable affordance Hand-Object Interaction (HOI) generation has become an increasingly important area of research in computer vision. In HOI generation, the hand grasp generation is a crucial step for effectively co…
Grasp GenerationMulti-GraspLLM: A Multimodal LLM for Multi-Hand Semantic Guided Grasp Generation
Multi-hand semantic grasp generation aims to generate feasible and semantically appropriate grasp poses for different robotic hands based on natural language instructions. Although the task is highly valuable, due to the…
Grasp GenerationRegionGrasp: A Novel Task for Contact Region Controllable Hand Grasp Generation
Can machine automatically generate multiple distinct and natural hand grasps, given specific contact region of an object in 3D? This motivates us to consider a novel task of \textit{Region Controllable Hand Grasp Generat…
Grasp GenerationObjectMulti-Modal Diffusion for Hand-Object Grasp Generation
In this work, we focus on generating hand grasp over objects. Compared to previous works of generating hand poses with a given object, we aim to allow the generalization of both hand and object shapes by a single model. …
DiversityGrasp GenerationObjectLearning Precise Affordances from Egocentric Videos for Robotic Manipulation
Affordance, defined as the potential actions that an object offers, is crucial for robotic manipulation tasks. A deep understanding of affordance can lead to more intelligent AI systems. For example, such knowledge direc…
Grasp GenerationDeep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations
Learning from Demonstrations, the field that proposes to learn robot behavior models from data, is gaining popularity with the emergence of deep generative models. Although the problem has been studied for years under na…
Grasp GenerationImitation LearningSurveyClickDiff: Click to Induce Semantic Contact Map for Controllable Grasp Generation with Diffusion Models
Grasp generation aims to create complex hand-object interactions with a specified object. While traditional approaches for hand generation have primarily focused on visibility and diversity under scene constraints, they …
Controllable Grasp GenerationGrasp GenerationObjectDecomposed Vector-Quantized Variational Autoencoder for Human Grasp Generation
Generating realistic human grasps is a crucial yet challenging task for applications involving object manipulation in computer graphics and robotics. Existing methods often struggle with generating fine-grained realistic…
Grasp GenerationNL2Contact: Natural Language Guided 3D Hand-Object Contact Modeling with Diffusion Model
Modeling the physical contacts between the hand and object is standard for refining inaccurate hand poses and generating novel human grasp in 3D hand-object reconstruction. However, existing methods rely on geometric con…
DescriptiveGrasp GenerationObjectObject ReconstructionHUP-3D: A 3D multi-view synthetic dataset for assisted-egocentric hand-ultrasound pose estimation
We present HUP-3D, a 3D multi-view multi-modal synthetic dataset for hand-ultrasound (US) probe pose estimation in the context of obstetric ultrasound. Egocentric markerless 3D joint pose estimation has potential applica…
DiversityGrasp GenerationMixed RealityPose EstimationSplat-MOVER: Multi-Stage, Open-Vocabulary Robotic Manipulation via Editable Gaussian Splatting
We present Splat-MOVER, a modular robotics stack for open-vocabulary robotic manipulation, which leverages the editability of Gaussian Splatting (GSplat) scene representations to enable multi-stage manipulation tasks. Sp…
Grasp GenerationSimulated Gaussian ManipulationSingle-View Scene Point Cloud Human Grasp Generation
In this work, we explore a novel task of generating human grasps based on single-view scene point clouds, which more accurately mirrors the typical real-world situation of observing objects from a single viewpoint. Due t…
Grasp GenerationObject