Arsalan Mousavian

research

∙ 04/18/2023

CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generation

We address the important problem of generalizing robotic rearrangement t...

0 Adithyavairavan Murali, et al. ∙

research

∙ 02/21/2023

Constrained Generative Sampling of 6-DoF Grasps

Most state-of-the-art data-driven grasp sampling methods propose stable ...

0 Jens Lundell, et al. ∙

research

∙ 12/13/2022

MegaPose: 6D Pose Estimation of Novel Objects via Render Compare

We introduce MegaPose, a method to estimate the 6D pose of novel objects...

0 Yann Labbé, et al. ∙

research

∙ 10/24/2022

Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation

Dexterous robotic hands have the capability to interact with a wide vari...

0 Zoey Qiuyu Chen, et al. ∙

research

∙ 09/28/2022

DexTransfer: Real World Multi-fingered Dexterous Grasping with Minimal Human Demonstrations

Teaching a multi-fingered dexterous robot to grasp objects in the real w...

4 Zoey Qiuyu Chen, et al. ∙

research

∙ 09/22/2022

ProgPrompt: Generating Situated Robot Task Plans using Large Language Models

Task planning can require defining myriad domain knowledge about the wor...

1 Ishika Singh, et al. ∙

research

∙ 07/06/2022

Deep Learning Approaches to Grasp Synthesis: A Review

Grasping is the process of picking an object by applying forces and torq...

0 Rhys Newbury, et al. ∙

research

∙ 02/01/2022

IFOR: Iterative Flow Minimization for Robotic Object Rearrangement

Accurate object rearrangement from vision is a crucial problem for a wid...

6 Ankit Goyal, et al. ∙

research

∙ 06/29/2021

RICE: Refining Instance Masks in Cluttered Environments with Graph Neural Networks

Segmenting unseen object instances in cluttered environments is an impor...

9 Christopher Xie, et al. ∙

research

∙ 06/02/2021

NeRP: Neural Rearrangement Planning for Unknown Objects

Robots will be expected to manipulate a wide variety of objects in compl...

42 Ahmed H. Qureshi, et al. ∙

research

∙ 04/28/2021

Fast Joint Space Model-Predictive Control for Reactive Manipulation

Sampling-based model predictive control (MPC) is a promising tool for fe...

0 Mohak Bhardwaj, et al. ∙

research

∙ 04/01/2021

RGB-D Local Implicit Function for Depth Completion of Transparent Objects

Majority of the perception methods in robotics require depth information...

25 Luyang Zhu, et al. ∙

research

∙ 03/31/2021

Sim-to-Real for Robotic Tactile Sensing via Physics-Based Simulation and Learned Latent Projections

Tactile sensing is critical for robotic grasping and manipulation of obj...

0 Yashraj Narang, et al. ∙

research

∙ 03/25/2021

Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes

Grasping unseen objects in unconstrained, cluttered environments is an e...

6 Martin Sundermeyer, et al. ∙

research

∙ 01/14/2021

Interpreting and Predicting Tactile Signals for the SynTouch BioTac

In the human hand, high-density contact information provided by afferent...

0 Yashraj S. Narang, et al. ∙

research

∙ 11/21/2020

Object Rearrangement Using Learned Implicit Collision Functions

Robotic object rearrangement combines the skills of picking and placing ...

3 Michael Danielczuk, et al. ∙

research

∙ 11/18/2020

ACRONYM: A Large-Scale Grasp Dataset Based on Simulation

We introduce ACRONYM, a dataset for robot grasp planning based on physic...

6 Clemens Eppner, et al. ∙

research

∙ 11/17/2020

Reactive Human-to-Robot Handovers of Arbitrary Objects

Human-robot object handovers have been an actively studied area of robot...

2 Wei Yang, et al. ∙

research

∙ 11/17/2020

Sim-to-Real Task Planning and Execution from Perception via Reactivity and Recovery

Zero-shot execution of unseen robotic tasks is an important problem in r...

7 Shohin Mukherjee, et al. ∙

research

∙ 07/30/2020

Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation

Segmenting unseen objects in cluttered scenes is an important skill that...

12 Yu Xiang, et al. ∙

research

∙ 07/16/2020

Unseen Object Instance Segmentation for Robotic Environments

In order to function in unstructured environments, robots need the abili...

21 Christopher Xie, et al. ∙

research

∙ 06/06/2020

Interpreting and Predicting Tactile Signals via a Physics-Based and Data-Driven Framework

High-density afferents in the human hand have long been regarded as esse...

0 Yashraj S. Narang, et al. ∙

research

∙ 12/11/2019

A Billion Ways to Grasp: An Evaluation of Grasp Sampling Schemes on a Dense, Physics-based Grasp Data Set

Robot grasping is often formulated as a learning problem. With the incre...

14 Clemens Eppner, et al. ∙

research

∙ 12/08/2019

6-DOF Grasping for Target-driven Object Manipulation in Clutter

Grasping in cluttered environments is a fundamental but challenging robo...

12 Adithyavairavan Murali, et al. ∙

research

∙ 12/01/2019

LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation

Current 6D object pose estimation methods usually require a 3D model for...

35 Keunhong Park, et al. ∙

research

∙ 09/23/2019

Self-supervised 6D Object Pose Estimation for Robot Manipulation

To teach robots skills, it is crucial to obtain data with supervision. S...

0 Xinke Deng, et al. ∙

research

∙ 07/30/2019

The Best of Both Modes: Separately Leveraging RGB and Depth for Unseen Object Instance Segmentation

In order to function in unstructured environments, robots need the abili...

4 Christopher Xie, et al. ∙

research

∙ 05/25/2019

6-DOF GraspNet: Variational Grasp Generation for Object Manipulation

Generating grasp poses is a crucial component for any robot object manip...

0 Arsalan Mousavian, et al. ∙

research

∙ 05/22/2019

PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking

Tracking 6D poses of objects from videos provides rich information to a ...

8 Xinke Deng, et al. ∙

research

∙ 05/15/2018

Visual Representations for Semantic Target Driven Navigation

What is a good visual representation for autonomous agents? We address t...

0 Arsalan Mousavian, et al. ∙

research

∙ 02/25/2017

Synthesizing Training Data for Object Detection in Indoor Scenes

Detection of objects in cluttered indoor environments is one of the key ...

0 Georgios Georgakis, et al. ∙

research

∙ 12/01/2016

3D Bounding Box Estimation Using Deep Learning and Geometry

We present a method for 3D object detection and pose estimation from a s...

0 Arsalan Mousavian, et al. ∙

research

∙ 09/26/2016

Multiview RGB-D Dataset for Object Instance Detection

This paper presents a new multi-view RGB-D dataset of nine kitchen scene...

0 Georgios Georgakis, et al. ∙

research

∙ 09/01/2016

Semantic Image Based Geolocation Given a Map

The problem visual place recognition is commonly used strategy for local...

0 Arsalan Mousavian, et al. ∙

research

∙ 04/25/2016

Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks

Multi-scale deep CNNs have been used successfully for problems mapping e...

0 Arsalan Mousavian, et al. ∙

Arsalan Mousavian

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