← Search

Gaurav Singh

14 accepted papers

2026

DAGDiff: Guiding Dual-Arm Grasp Diffusion to Stable and Collision-Free Grasps

ICRA 2026poster

Reliable dual-arm grasping is essential for manipulating large and complex objects but remains a challenging problem due to stability, collision, and generalization requirements. Prior methods typically decompose the task into two independent grasp proposals, relying on region priors or heuristics t…

2026

SceneComplete: Open-World 3D Scene Completion in Cluttered Real World Environments for Robot Manipulation

RA-L 2026

Careful robot manipulation in every-day cluttered environments requires an accurate understanding of the 3D scene, in order to grasp and place objects stably and reliably and to avoid colliding with other objects. In general, we must construct such a 3D interpretation of a complex scene based on lim

Cited by 11SourcecodeScholar
2026

SceneComplete: Open-World 3D Scene Completion in Cluttered Real World Environments for Robot Manipulation

ICRA 2026poster

Careful robot manipulation in every-day cluttered environments requires an accurate understanding of the 3D scene, in order to grasp and place objects stably and reliably and to avoid colliding with other objects. In general, we must construct such a 3D interpretation of a complex scene based on lim…

2025

DG16M: A Large-Scale Dataset for Dual-Arm Grasping with Force-Optimized Grasps

IROS 2025

Dual-arm robotic grasping is crucial for handling large objects that require stable and coordinated manipulation. While single-arm grasping has been extensively studied, datasets tailored for dual-arm settings remain scarce. We introduce a large-scale dataset of 16 million dual-arm grasps, evaluated

Cited by 4SourcecodeScholar
2025

Da-Vil: Adaptive Dual-Arm Manipulation with Reinforcement Learning and Variable Impedance Control

ICRA 2025

Dual-arm manipulation is an area of growing interest in the robotics community. Enabling robots to perform tasks that require the coordinated use of two arms, is essential for complex manipulation tasks such as handling large objects, assembling components, and performing human-like interactions. Ho

Cited by 13SourcecodeScholar
2024

Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation

IROS 2024poster

Efficiently generating grasp poses tailored to specific regions of an object is vital for various robotic manipulation tasks, especially in a dual-arm setup. This scenario presents a significant challenge due to the complex geometries involved, requiring a deep understanding of the local geometry to…

Cited by 6SourcecodeScholar
2024

On Hardware-efficient Inference in Probabilistic Circuits

UAI 2024poster

Probabilistic circuits (PCs) offer a promising avenue to perform embedded reasoning under uncertainty. They support efficient and exact computation of various probabilistic inference tasks by design. Hence, hardware-efficient computation of PCs is highly interesting for edge computing applications.…

Cited by 0SourcePDFScholar
2023

HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork

NeurIPS 2023poster

Neural Radiance Fields (NeRF) have become an increasingly popular representation to capture high-quality appearance and shape of scenes and objects. However, learning generalizable NeRF priors over categories of scenes or objects has been challenging due to the high dimensionality of network weight…

Cited by 13SourcePDFScholar
2023

MailEx: Email Event and Argument Extraction

EMNLP 2023long main

In this work, we present the first dataset, MailEx, for performing event extraction from conversational email threads. To this end, we first proposed a new taxonomy covering 10 event types and 76 arguments in the email domain. Our final dataset includes 1.5K email threads and ~4K emails, which are a…

Cited by 0SourcecodeScholar
2023

SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping

ICRA 2023poster

Recovering full 3D shapes from partial observations is a challenging task that has been extensively addressed in the computer vision community. Many deep learning methods tackle this problem by training 3D shape generation networks to learn a prior over the full 3D shapes. In this training regime, t…

Cited by 14SourcecodeScholar
2022

A Relation Extraction Dataset for Knowledge Extraction from Web Tables

COLING 2022main

Relational web-tables are significant sources of structural information that are widely used for relation extraction and population of facts into knowledge graphs. To transform the web-table data into knowledge, we need to identify the relations that exist between column pairs. Currently, there are…

2022

Finite Element Modeling of Internally Actuated Triangular Lattice and Its Variants for Modular Active Cell Robots (MACROs)

RA-L 2022

Modular Active Cell Robots (MACROs) is an approach for modular robot hardware that leverages simple components such as actuators and compliant joints to make large deformable robotic structures. In this letter, we consider the planar triangular lattice and its sparser variants as the candidate mesh

Cited by 2SourceScholar
2015

An isoperimetric formulation to predict deformation behavior of pneumatic fiber reinforced elastomeric actuators

IROS 2015poster

Fiber reinforced elastomeric actuators are popular actuators for soft robots because of their inherent safety, energy density and a large repertoire of spatial motion patterns. However, a small subset of these actuators alone known as McKibben pneumatic muscles with antisymmetric fiber orientations…

Cited by 38SourceScholar