6 papers
SLAMSqueezeBench: Comparing SLAM Systems under Resource Constraints
Mohamed Hefny, Karthik Dantu, Steven Y. Ko
Simultaneous localization and mapping (SLAM) is one of the services running on an autonomous robot. It is typically run to assist other tasks such as planning, manipulation, etc. A…
FastLoop: Parallel Loop Closing with GPU-Acceleration in Visual SLAM
Soudabeh Mohammadhashemi, Shishir Gopinath, Kimia Khabiri +3
Visual SLAM systems combine visual tracking with global loop closure to maintain a consistent map and accurate localization. Loop closure is a computationally expensive process as…
SLAM Adversarial Lab: An Extensible Framework for Visual SLAM Robustness Evaluation under Adverse Conditions
Mohamed Hefny, Karthik Dantu, Steven Y. Ko
We present SAL (SLAM Adversarial Lab), a modular framework for evaluating visual SLAM systems under adversarial conditions such as fog and rain. SAL represents each adversarial con…
TurboMap: GPU-Accelerated Local Mapping for Visual SLAM
Parsa Hosseininejad, Kimia Khabiri, Shishir Gopinath +3
In real-time Visual SLAM systems, local mapping must operate under strict latency constraints, as delays degrade map quality and increase the risk of tracking failure. GPU parallel…
Graphite: A GPU-Accelerated Mixed-Precision Graph Optimization Framework
Shishir Gopinath, Karthik Dantu, Steven Y. Ko
We present Graphite, a GPU-accelerated nonlinear least squares graph optimization framework. It provides a CUDA C++ interface to enable the sharing of code between a real-time appl…
FastTrack: GPU-Accelerated Tracking for Visual SLAM
Kimia Khabiri, Parsa Hosseininejad, Shishir Gopinath +2
The tracking module of a visual-inertial SLAM system processes incoming image frames and IMU data to estimate the position of the frame in relation to the map. It is important for…