Papers Deformable Object Manipulation
“Deformable Object Manipulation” 태그가 달린 논문 44편 · 필터 해제
EC-Flow: Enabling Versatile Robotic Manipulation from Action-Unlabeled Videos via Embodiment-Centric Flow
Current language-guided robotic manipulation systems often require low-level action-labeled datasets for imitation learning. While object-centric flow prediction methods mitigate this issue, they remain limited to scenar…
Deformable Object ManipulationImitation LearningObjectManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation
Vision-Language Models (VLMs) have revolutionized artificial intelligence and robotics due to their commonsense reasoning capabilities. In robotic manipulation, VLMs are used primarily as high-level planners, but recent …
BenchmarkingDeformable Object ManipulationObjectRobot ManipulationImplicit Neural-Representation Learning for Elastic Deformable-Object Manipulations
We aim to solve the problem of manipulating deformable objects, particularly elastic bands, in real-world scenarios. However, deformable object manipulation (DOM) requires a policy that works on a large state space due t…
Deformable Object ManipulationReinforcement Learning (RL)Representation LearningPhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videos
Creating a physical digital twin of a real-world object has immense potential in robotics, content creation, and XR. In this paper, we present PhysTwin, a novel framework that uses sparse videos of dynamic objects under …
4D reconstructionDeformable Object ManipulationFuture predictionMotion Planning+1One-Shot Affordance Grounding of Deformable Objects in Egocentric Organizing Scenes
Deformable object manipulation in robotics presents significant challenges due to uncertainties in component properties, diverse configurations, visual interference, and ambiguous prompts. These factors complicate both p…
Deformable Object ManipulationDifferentiable Information Enhanced Model-Based Reinforcement Learning
Differentiable environments have heralded new possibilities for learning control policies by offering rich differentiable information that facilitates gradient-based methods. In comparison to prevailing model-free reinfo…
Deformable Object ManipulationmodelModel-based Reinforcement Learningreinforcement-learning+1Robot Deformable Object Manipulation via NMPC-generated Demonstrations in Deep Reinforcement Learning
In this work, we conducted research on deformable object manipulation by robots based on demonstration-enhanced reinforcement learning (RL). To improve the learning efficiency of RL, we enhanced the utilization of demons…
Deep Reinforcement LearningDeformable Object ManipulationModel Predictive ControlReinforcement Learning (RL)+1DeformPAM: Data-Efficient Learning for Long-horizon Deformable Object Manipulation via Preference-based Action Alignment
In recent years, imitation learning has made progress in the field of robotic manipulation. However, it still faces challenges when addressing complex long-horizon tasks with deformable objects, such as high-dimensional …
Deformable Object ManipulationImitation LearningD-Cubed: Latent Diffusion Trajectory Optimisation for Dexterous Deformable Manipulation
Mastering dexterous robotic manipulation of deformable objects is vital for overcoming the limitations of parallel grippers in real-world applications. Current trajectory optimisation approaches often struggle to solve s…
Deformable Object ManipulationDeformGS: Scene Flow in Highly Deformable Scenes for Deformable Object Manipulation
Teaching robots to fold, drape, or reposition deformable objects such as cloth will unlock a variety of automation applications. While remarkable progress has been made for rigid object manipulation, manipulating deforma…
Deformable Object ManipulationImitation LearningNovel View SynthesisPose EstimationRegistered and Segmented Deformable Object Reconstruction from a Single View Point Cloud
In deformable object manipulation, we often want to interact with specific segments of an object that are only defined in non-deformed models of the object. We thus require a system that can recognize and locate these se…
Deformable Object ManipulationObjectObject ReconstructionMake a Donut: Hierarchical EMD-Space Planning for Zero-Shot Deformable Manipulation with Tools
Deformable object manipulation stands as one of the most captivating yet formidable challenges in robotics. While previous techniques have predominantly relied on learning latent dynamics through demonstrations, typicall…
Deformable Object ManipulationModel Predictive ControlLearning Generalizable Tool-use Skills through Trajectory Generation
Autonomous systems that efficiently utilize tools can assist humans in completing many common tasks such as cooking and cleaning. However, current systems fall short of matching human-level of intelligence in terms of ad…
Deformable Object ManipulationDefGoalNet: Contextual Goal Learning from Demonstrations For Deformable Object Manipulation
Shape servoing, a robotic task dedicated to controlling objects to desired goal shapes, is a promising approach to deformable object manipulation. An issue arises, however, with the reliance on the specification of a goa…
Deformable Object ManipulationObjectGenDOM: Generalizable One-shot Deformable Object Manipulation with Parameter-Aware Policy
Due to the inherent uncertainty in their deformability during motion, previous methods in deformable object manipulation, such as rope and cloth, often required hundreds of real-world demonstrations to train a manipulati…
Deformable Object ManipulationObjectSculptBot: Pre-Trained Models for 3D Deformable Object Manipulation
Deformable object manipulation presents a unique set of challenges in robotic manipulation by exhibiting high degrees of freedom and severe self-occlusion. State representation for materials that exhibit plastic behavior…
Deformable Object ManipulationObjectPoint cloud reconstructionDexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics
In this work, we aim to learn dexterous manipulation of deformable objects using multi-fingered hands. Reinforcement learning approaches for dexterous rigid object manipulation would struggle in this setting due to the c…
Deformable Object ManipulationObjectLearning Foresightful Dense Visual Affordance for Deformable Object Manipulation
Understanding and manipulating deformable objects (e.g., ropes and fabrics) is an essential yet challenging task with broad applications. Difficulties come from complex states and dynamics, diverse configurations and hig…
Deformable Object ManipulationObjectRobotic Fabric Flattening with Wrinkle Direction Detection
Deformable Object Manipulation (DOM) is an important field of research as it contributes to practical tasks such as automatic cloth handling, cable routing, surgical operation, etc. Perception is considered one of the ma…
Deformable Object ManipulationImitation Learning As State Matching via Differentiable Physics
Existing imitation learning (IL) methods such as inverse reinforcement learning (IRL) usually have a double-loop training process, alternating between learning a reward function and a policy and tend to suffer long t…
continuous-controlContinuous ControlDeformable Object ManipulationImitation Learning