9 citations · 15 across the 24 of their papers we have counts for
28 papers
Weakly Supervised Fish Segmentation through Point-Supervised Tracking and Motion-Informed Language
Vedanth Kallakuri, Katherine A. Skinner
Understanding the properties of fish populations is increasingly important. Analyzing fish length, width, and mass is integral to maintaining healthy stock in the aquaculture indus…
Towards Scaling Marine Perception with Synthetic Data
Haoyu Ma, Onur Bagoren, Anja Sheppard +6
Scalable machine learning in challenging underwater environments is strongly limited by the lack of labeled real-world training data. This data is often expensive and laborious to…
STAR-VLM: Spatiotemporal Grounding Vision-Language Models for Motion and Velocity Estimation via Automotive Radar Supervision
Pou-Chun Kung, Aryaman Rao, Utkrisht Sahai +4
Vision-language models (VLMs) are emerging as a key component of embodied intelligence, with growing applications in auto-labeling and end-to-end autonomous driving. However, exist…
CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining
Jingyu Song, Yi Liu, Katherine A. Skinner
Camera-radar (CR) fusion is a practical sensing configuration for autonomous driving, but existing models are typically trained with task-specific supervision, limiting reusable re…
TRGS-SLAM: IMU-Aided Gaussian Splatting SLAM for Blurry, Rolling Shutter, and Noisy Thermal Images
Spencer Carmichael, Katherine A. Skinner
Thermal cameras offer several advantages for simultaneous localization and mapping (SLAM) with mobile robots: they provide a passive, low-power solution to operating in darkness, a…
SurfSLAM: Sim-to-Real Underwater Stereo Reconstruction For Real-Time SLAM
Onur Bagoren, Seth Isaacson, Sacchin Sundar +6
Localization and mapping are core perceptual capabilities for underwater robots. Stereo cameras provide a low-cost means of directly estimating metric depth to support these tasks.…
SLIM-VDB: A Real-Time 3D Probabilistic Semantic Mapping Framework
Anja Sheppard, Parker Ewen, Joey Wilson +6
This paper introduces SLIM-VDB, a new lightweight semantic mapping system with probabilistic semantic fusion for closed-set or open-set dictionaries. Advances in data structures fr…
A Stochastic Approach to Terrain Maps for Safe Lunar Landing
Anja Sheppard, Chris Reale, Katherine A. Skinner
Safely landing on the lunar surface is a challenging task, especially in the heavily-shadowed South Pole region where traditional vision-based hazard detection methods are not reli…
FishDetector-R1: Unified MLLM-Based Framework with Reinforcement Fine-Tuning for Weakly Supervised Fish Detection, Segmentation, and Counting
Yi Liu, Jingyu Song, Vedanth Kallakuri +1
Analyzing underwater fish imagery is critical for ecological monitoring but remains difficult due to visual degradation and costly annotations. We introduce FishDetector-R1, a unif…
DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models
Jingyu Song, Zhenxin Li, Shiyi Lan +6
Benchmarking autonomous driving planners to align with human judgment remains a critical challenge, as state-of-the-art metrics like the Extended Predictive Driver Model Score (EPD…
ShipwreckFinder: A QGIS Tool for Shipwreck Detection in Multibeam Sonar Data
Anja Sheppard, Tyler Smithline, Andrew Scheffer +5
In this paper, we introduce ShipwreckFinder, an open-source QGIS plugin that detects shipwrecks from multibeam sonar data. Shipwrecks are an important historical marker of maritime…
Field Report on Ground Penetrating Radar for Localization at the Mars Desert Research Station
Anja Sheppard, Katherine A. Skinner
In this field report, we detail the lessons learned from our field expedition to collect Ground Penetrating Radar (GPR) data in a Mars analog environment for the purpose of validat…
SonarSplat: Novel View Synthesis of Imaging Sonar via Gaussian Splatting
Advaith V. Sethuraman, Max Rucker, Onur Bagoren +3
In this paper, we present SonarSplat, a novel Gaussian splatting framework for imaging sonar that demonstrates realistic novel view synthesis and models acoustic streaking phenomen…
MarsLGPR: Mars Rover Localization with Ground Penetrating Radar
Anja Sheppard, Katherine A. Skinner
In this work, we propose the use of Ground Penetrating Radar (GPR) for rover localization on Mars. Precise pose estimation is an important task for mobile robots exploring planetar…
OceanSim: A GPU-Accelerated Underwater Robot Perception Simulation Framework
Jingyu Song, Haoyu Ma, Onur Bagoren +3
Underwater simulators offer support for building robust underwater perception solutions. Significant work has recently been done to develop new simulators and to advance the perfor…
PUGS: Perceptual Uncertainty for Grasp Selection in Underwater Environments
Onur Bagoren, Marc Micatka, Katherine A. Skinner +1
When navigating and interacting in challenging environments where sensory information is imperfect and incomplete, robots must make decisions that account for these shortcomings. W…
LiHi-GS: LiDAR-Supervised Gaussian Splatting for Highway Driving Scene Reconstruction
Pou-Chun Kung, Xianling Zhang, Katherine A. Skinner +1
Photorealistic 3D scene reconstruction plays an important role in autonomous driving, enabling the generation of novel data from existing datasets to simulate safety-critical scena…
VAIR: Visuo-Acoustic Implicit Representations for Low-Cost, Multi-Modal Transparent Surface Reconstruction in Indoor Scenes
Advaith V. Sethuraman, Onur Bagoren, Harikrishnan Seetharaman +3
Mobile robots operating indoors must be prepared to navigate challenging scenes that contain transparent surfaces. This paper proposes a novel method for the fusion of acoustic and…
MemFusionMap: Working Memory Fusion for Online Vectorized HD Map Construction
Jingyu Song, Xudong Chen, Liupei Lu +2
High-definition (HD) maps provide environmental information for autonomous driving systems and are essential for safe planning. While existing methods with single-frame input achie…
TURTLMap: Real-time Localization and Dense Mapping of Low-texture Underwater Environments with a Low-cost Unmanned Underwater Vehicle
Jingyu Song, Onur Bagoren, Razan Andigani +2
Significant work has been done on advancing localization and mapping in underwater environments. Still, state-of-the-art methods are challenged by low-texture environments, which i…
Learning Surface Terrain Classifications from Ground Penetrating Radar
Anja Sheppard, Jason Brown, Nilton Renno +1
Terrain classification is an important problem for mobile robots operating in extreme environments as it can aid downstream tasks such as autonomous navigation and planning. While…
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation
Lingjun Zhao, Jingyu Song, Katherine A. Skinner
In the field of 3D object detection for autonomous driving, LiDAR-Camera (LC) fusion is the top-performing sensor configuration. Still, LiDAR is relatively high cost, which hinders…
A Detection and Filtering Framework for Collaborative Localization
Thirumalaesh Ashokkumar, Katherine A Skinner, Siddarth Agarwal +2
Increasingly, autonomous vehicles (AVs) are becoming a reality, such as the Advanced Driver Assistance Systems (ADAS) in vehicles that assist drivers in driving and parking functio…
LiRaFusion: Deep Adaptive LiDAR-Radar Fusion for 3D Object Detection
Jingyu Song, Lingjun Zhao, Katherine A. Skinner
We propose LiRaFusion to tackle LiDAR-radar fusion for 3D object detection to fill the performance gap of existing LiDAR-radar detectors. To improve the feature extraction capabili…