22 citations · 38 across the 20 of their papers we have counts for
21 papers
PILOT: Guiding Long-Horizon World-Model Planning for Robot Manipulation with Visual Subgoals and Policy Priors
Yang Liu, Hanchen Cui, Karthik Desingh
Latent world-model planning has shown promising results in goal-conditioned robotic manipulation, but remains challenging for long-horizon planning due to limited temporal guidance…
Active Real-World Factor-Based Evaluation for Generalist Robot Policies
Andrew Liao, Hanchen Cui, Karthik Desingh +1
Generalist robot manipulation policies trained on large, diverse datasets have shown remarkable promise across a wide range of tasks. However, rigorously evaluating these policies…
DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning
Hanchen Cui, Sergio Arnaud, Arjun Majumdar +5
Pretrained vision-language-action (VLA) policies show promising zero-shot generalization, but often fail under deployment-time distribution shift, leading to decreased robustness a…
Learning Category-level Last-meter Navigation from RGB Demonstrations of a Single-instance
Tzu-Hsien Lee, Fidan Mahmudova, Karthik Desingh
Achieving precise positioning of the mobile manipulator's base is essential for successful manipulation actions that follow. Most of the RGB-based navigation systems only guarantee…
SENT Map -- Semantically Enhanced Topological Maps with Foundation Models
Raj Surya Rajendran Kathirvel, Zach A Chavis, Stephen J. Guy +1
We introduce SENT-Map, a semantically enhanced topological map for representing indoor environments, designed to support autonomous navigation and manipulation by leveraging advanc…
SPARK-Remote: A Cost-Effective System for Remote Bimanual Robot Teleoperation
Adam Imdieke, Karthik Desingh
Robot teleoperation enables human control over robotic systems in environments where full autonomy is challenging. Recent advancements in low-cost teleoperation devices and VR/AR t…
SuperQ-GRASP: Superquadrics-based Grasp Pose Estimation on Larger Objects for Mobile-Manipulation
Xun Tu, Karthik Desingh
Grasp planning and estimation have been a longstanding research problem in robotics, with two main approaches to find graspable poses on the objects: 1) geometric approach, which r…
AugInsert: Learning Robust Visual-Force Policies via Data Augmentation for Object Assembly Tasks
Ryan Diaz, Adam Imdieke, Vivek Veeriah +1
Operating in unstructured environments like households requires robotic policies that are robust to out-of-distribution conditions. Although much work has been done in evaluating r…
Talk Through It: End User Directed Manipulation Learning
Carl Winge, Adam Imdieke, Bahaa Aldeeb +2
Training generalist robot agents is an immensely difficult feat due to the requirement to perform a huge range of tasks in many different environments. We propose selectively train…
SlotGNN: Unsupervised Discovery of Multi-Object Representations and Visual Dynamics
Alireza Rezazadeh, Athreyi Badithela, Karthik Desingh +1
Learning multi-object dynamics from visual data using unsupervised techniques is challenging due to the need for robust, object representations that can be learned through robot in…
Evaluating Robustness of Visual Representations for Object Assembly Task Requiring Spatio-Geometrical Reasoning
Chahyon Ku, Carl Winge, Ryan Diaz +2
This paper primarily focuses on evaluating and benchmarking the robustness of visual representations in the context of object assembly tasks. Specifically, it investigates the alig…
DNBP: Differentiable Nonparametric Belief Propagation
Anthony Opipari, Jana Pavlasek, Chao Chen +3
We present a differentiable approach to learn the probabilistic factors used for inference by a nonparametric belief propagation algorithm. Existing nonparametric belief propagatio…
Break and Make: Interactive Structural Understanding Using LEGO Bricks
Aaron Walsman, Muru Zhang, Klemen Kotar +3
Visual understanding of geometric structures with complex spatial relationships is a fundamental component of human intelligence. As children, we learn how to reason about structur…
SORNet: Spatial Object-Centric Representations for Sequential Manipulation
Wentao Yuan, Chris Paxton, Karthik Desingh +1
Sequential manipulation tasks require a robot to perceive the state of an environment and plan a sequence of actions leading to a desired goal state. In such tasks, the ability to…
LanguageRefer: Spatial-Language Model for 3D Visual Grounding
Junha Roh, Karthik Desingh, Ali Farhadi +1
For robots to understand human instructions and perform meaningful tasks in the near future, it is important to develop learned models that comprehend referential language to ident…
Differentiable Nonparametric Belief Propagation
Anthony Opipari, Chao Chen, Shoutian Wang +3
We present a differentiable approach to learn the probabilistic factors used for inference by a nonparametric belief propagation algorithm. Existing nonparametric belief propagatio…
Parts-Based Articulated Object Localization in Clutter Using Belief Propagation
Jana Pavlasek, Stanley Lewis, Karthik Desingh +1
Robots working in human environments must be able to perceive and act on challenging objects with articulations, such as a pile of tools. Articulated objects increase the dimension…
A Sketch-Based System for Human-Guided Constrained Object Manipulation
Sina Masnadi, Joseph J. LaViola, Xiaofan Zhu +2
In this paper, we present an easy to use sketch-based interface to extract geometries and generate affordance files from 3D point clouds for robot-object interaction tasks. Using o…
Factored Pose Estimation of Articulated Objects using Efficient Nonparametric Belief Propagation
Karthik Desingh, Shiyang Lu, Anthony Opipari +1
Robots working in human environments often encounter a wide range of articulated objects, such as tools, cabinets, and other jointed objects. Such articulated objects can take an i…
Semantic Mapping with Simultaneous Object Detection and Localization
Zhen Zeng, Yunwen Zhou, Odest Chadwicke Jenkins +1
We present a filtering-based method for semantic mapping to simultaneously detect objects and localize their 6 degree-of-freedom pose. For our method, called Contextual Temporal Ma…
Pull Message Passing for Nonparametric Belief Propagation
Karthik Desingh, Anthony Opipari, Odest Chadwicke Jenkins
We present a "pull" approach to approximate products of Gaussian mixtures within message updates for Nonparametric Belief Propagation (NBP) inference. Existing NBP methods often re…