221 citations · 621 across the 9 of their papers we have counts for
13 papers
droidlet: modular, heterogenous, multi-modal agents
Anurag Pratik, Soumith Chintala, Kavya Srinet +10
In recent years, there have been significant advances in building end-to-end Machine Learning (ML) systems that learn at scale. But most of these systems are: (a) isolated (percept…
Visual Imitation Made Easy
Sarah Young, Dhiraj Gandhi, Shubham Tulsiani +3
Visual imitation learning provides a framework for learning complex manipulation behaviors by leveraging human demonstrations. However, current interfaces for imitation such as kin…
Swoosh! Rattle! Thump! -- Actions that Sound
Dhiraj Gandhi, Abhinav Gupta, Lerrel Pinto
Truly intelligent agents need to capture the interplay of all their senses to build a rich physical understanding of their world. In robotics, we have seen tremendous progress in u…
Object Goal Navigation using Goal-Oriented Semantic Exploration
Devendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta +1
This work studies the problem of object goal navigation which involves navigating to an instance of the given object category in unseen environments. End-to-end learning-based navi…
Learning to Explore using Active Neural SLAM
Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta +2
This work presents a modular and hierarchical approach to learn policies for exploring 3D environments, called `Active Neural SLAM'. Our approach leverages the strengths of both cl…
Object-centric Forward Modeling for Model Predictive Control
Yufei Ye, Dhiraj Gandhi, Abhinav Gupta +1
We present an approach to learn an object-centric forward model, and show that this allows us to plan for sequences of actions to achieve distant desired goals. We propose to model…
PyRobot: An Open-source Robotics Framework for Research and Benchmarking
Adithyavairavan Murali, Tao Chen, Kalyan Vasudev Alwala +4
This paper introduces PyRobot, an open-source robotics framework for research and benchmarking. PyRobot is a light-weight, high-level interface on top of ROS that provides a consis…
Self-Supervised Exploration via Disagreement
Deepak Pathak, Dhiraj Gandhi, Abhinav Gupta
Efficient exploration is a long-standing problem in sensorimotor learning. Major advances have been demonstrated in noise-free, non-stochastic domains such as video games and simul…
Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
Abhinav Gupta, Adithyavairavan Murali, Dhiraj Gandhi +1
Data-driven approaches to solving robotic tasks have gained a lot of traction in recent years. However, most existing policies are trained on large-scale datasets collected in cura…
Learning to Grasp Without Seeing
Adithyavairavan Murali, Yin Li, Dhiraj Gandhi +1
Can a robot grasp an unknown object without seeing it? In this paper, we present a tactile-sensing based approach to this challenging problem of grasping novel objects without prio…
CASSL: Curriculum Accelerated Self-Supervised Learning
Adithyavairavan Murali, Lerrel Pinto, Dhiraj Gandhi +1
Recent self-supervised learning approaches focus on using a few thousand data points to learn policies for high-level, low-dimensional action spaces. However, scaling this framewor…
Learning to Fly by Crashing
Dhiraj Gandhi, Lerrel Pinto, Abhinav Gupta
How do you learn to navigate an Unmanned Aerial Vehicle (UAV) and avoid obstacles? One approach is to use a small dataset collected by human experts: however, high capacity learnin…
The Curious Robot: Learning Visual Representations via Physical Interactions
Lerrel Pinto, Dhiraj Gandhi, Yuanfeng Han +2
What is the right supervisory signal to train visual representations? Current approaches in computer vision use category labels from datasets such as ImageNet to train ConvNets. Ho…