GATSBI: An Online GTSP-Based Algorithm for Targeted Surface Bridge Inspection and Defect Detection
Harnaik Dhami, Charith Reddy, Vishnu Dutt Sharma, Troi Williams,, Pratap Tokekar

TL;DR
GATSBI is an online UAV path planning algorithm that uses GTSP to efficiently inspect infrastructure surfaces for defects without prior geometric models, adapting in real-time based on sensor data.
Contribution
This paper introduces GATSBI, a novel real-time inspection planning method that integrates GTSP with UAV surface inspection using online 3D mapping and semantic segmentation.
Findings
GATSBI outperforms baseline methods in inspection efficiency.
The algorithm effectively replans paths as new environment data is acquired.
Simulation and real-world tests validate the approach's robustness.
Abstract
We study the problem of visual surface inspection of infrastructure for defects using an Unmanned Aerial Vehicle (UAV). We do not assume that the geometric model of the infrastructure is known beforehand. Our planner, termed GATSBI, plans a path in a receding horizon fashion to inspect all points on the surface of the infrastructure. The input to GATSBI consists of a 3D occupancy map created online with 3D pointclouds. Occupied voxels corresponding to the infrastructure in this map are semantically segmented and used to create an infrastructure-only occupancy map. Inspecting an infrastructure voxel requires the UAV to take images from a desired viewing angle and distance. We then create a Generalized Traveling Salesperson Problem (GTSP) instance to cluster candidate viewpoints for inspecting the infrastructure voxels and use an off-the-shelf GTSP solver to find the optimal path for the…
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Taxonomy
TopicsInfrastructure Maintenance and Monitoring · Non-Destructive Testing Techniques · Industrial Vision Systems and Defect Detection
