2 citations · 3 across the 11 of their papers we have counts for
11 papers
VISTA: Scale-Aware Visual Navigation via Action History Conditioning
Maeva Guerrier, Koki Kobayashi, Simon Roy +2
Vision Navigation Foundation Models (VNMs) promise end-to-end learned navigation policies capable of zero-shot deployment across diverse embodiments and environments. To maintain g…
Can Vision Foundation Models Navigate? Zero-Shot Real-World Evaluation and Lessons Learned
Maeva Guerrier, Karthik Soma, Jana Pavlasek +1
Visual Navigation Models (VNMs) promise generalizable, robot navigation by learning from large-scale visual demonstrations. Despite growing real-world deployment, existing evaluati…
MBot: A Modular Ecosystem for Scalable Robotics Education
Peter Gaskell, Jana Pavlasek, Tom Gao +3
The Michigan Robotics MBot is a low-cost mobile robot platform that has been used to train over 1,400 students in autonomous navigation since 2014 at the University of Michigan and…
Stein Variational Belief Propagation for Multi-Robot Coordination
Jana Pavlasek, Joshua Jing Zhi Mah, Ruihan Xu +2
Decentralized coordination for multi-robot systems involves planning in challenging, high-dimensional spaces. The planning problem is particularly challenging in the presence of ob…
Counter-Hypothetical Particle Filters for Single Object Pose Tracking
Elizabeth A. Olson, Jana Pavlasek, Jasmine A. Berry +1
Particle filtering is a common technique for six degrees of freedom (6D) pose estimation due to its ability to tractably represent belief over object pose. However, the particle fi…
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…
NARF22: Neural Articulated Radiance Fields for Configuration-Aware Rendering
Stanley Lewis, Jana Pavlasek, Odest Chadwicke Jenkins
Articulated objects pose a unique challenge for robotic perception and manipulation. Their increased number of degrees-of-freedom makes tasks such as localization computationally d…
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…
Manipulation-Oriented Object Perception in Clutter through Affordance Coordinate Frames
Xiaotong Chen, Kaizhi Zheng, Zhen Zeng +5
In order to enable robust operation in unstructured environments, robots should be able to generalize manipulation actions to novel object instances. For example, to pour and serve…
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…