6 papers
An Open Source Computer Vision and Machine Learning Framework for Affordable Life Science Robotic Automation
Zachary Logan, Andrew Dudash, Daniel Negrón
We present an open-source robotic framework that integrates computer vision and machine learning based inverse kinematics to enable low-cost laboratory automation tasks such as col…
Soil Sample Search in Partially Observable Environments
Han Yang, Andrew Dudash
To work in unknown outdoor environments, autonomous sampling machines need the ability to target samples despite limited visibility and robotic arm reach distance. We design a heur…
Autonomous Soil Collection in Environments With Heterogeneous Terrain
Andrew Dudash, Beyonce Andrades, Ryan Rubel +3
To autonomously collect soil in uncultivated terrain, robotic arms must distinguish between different amorphous materials and submerge themselves into the correct material. We deve…
Multi-Agent Team Access Monitoring: Environments that Benefit from Target Information Sharing
Andrew Dudash, Scott James, Ryan Rubel
Robotic access monitoring of multiple target areas has applications including checkpoint enforcement, surveillance and containment of fire and flood hazards. Monitoring access for…
SurfaceAug: Closing the Gap in Multimodal Ground Truth Sampling
Ryan Rubel, Nathan Clark, Andrew Dudash
Despite recent advances in both model architectures and data augmentation, multimodal object detectors still barely outperform their LiDAR-only counterparts. This shortcoming has b…
Automated Multimodal Data Annotation via Calibration With Indoor Positioning System
Ryan Rubel, Andrew Dudash, Mohammad Goli +2
Learned object detection methods based on fusion of LiDAR and camera data require labeled training samples, but niche applications, such as warehouse robotics or automated infrastr…