
Katya Papais developed lidar-enabled navigation and mapping support for the utiasASRL/vtr3 repository, focusing on integrating Aeva lidar data into the VTR pipeline. She implemented a configuration-driven workflow using C++ and YAML, enabling ingestion and processing of Aeva lidar point clouds for robust perception tasks. Her work included defining sensor parameters, establishing frame transformations, and modularizing processing stages such as conversion, filtering, odometry, and localization. By introducing configuration files and preprocessing workflows, Katya facilitated both experimentation and deployment. The depth of her contribution lies in the seamless integration of lidar data, enhancing the system’s flexibility and supporting advanced embedded applications.
May 2025 monthly summary for utiasASRL/vtr3 focused on delivering lidar-enabled navigation and mapping support. Implemented Aeva lidar data integration through a configuration-driven workflow and C++ changes to ingest and process Aeva point clouds within the VTR pipeline. Established sensor parameter definitions, frame transformations, and modular processing stages (conversion, filtering, odometry, localization) to enable robust perception tasks.
May 2025 monthly summary for utiasASRL/vtr3 focused on delivering lidar-enabled navigation and mapping support. Implemented Aeva lidar data integration through a configuration-driven workflow and C++ changes to ingest and process Aeva point clouds within the VTR pipeline. Established sensor parameter definitions, frame transformations, and modular processing stages (conversion, filtering, odometry, localization) to enable robust perception tasks.

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