no code implementations • 12 Nov 2021 • Sriram Siva, Maggie Wigness, John G. Rogers, Long Quang, Hao Zhang
Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response.
3 code implementations • 17 Nov 2020 • Peng Jiang, Philip Osteen, Maggie Wigness, Srikanth Saripalli
The data was collected on the Rellis Campus of Texas A\&M University and presents challenges to existing algorithms related to class imbalance and environmental topography.
Ranked #1 on 3D Semantic Segmentation on RELLIS-3D Dataset
no code implementations • CVPR 2017 • Maggie Wigness, John G. Rogers III
We introduce an unsupervised semantic scene labeling approach that continuously learns and adapts semantic models discovered within a data stream.
no code implementations • CVPR 2015 • Maggie Wigness, Bruce A. Draper, J. Ross Beveridge
Finally, we demonstrate the speed and efficiency of our system using real-world data collected for an autonomous navigation task.