Nvidia Library Tasks: Stage 1

[Ishaan-Datta]

Dive into the Nvidia library ecosystem:

• Document what solutions are available Example
• Determine their feasibility with our project
• Find the input data requirements
• Find what sensors are most effective for the input data
• Find the output data format and how it relates to SLAM
• Make notes on the relative performance/benchmarks of each library (accuracy, speed, effectiveness)
• Make a report including your findings
• https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_map_localization/index.html
• https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_mapping_and_localization/index.html
• https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_nvblox/index.html
• https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_visual_slam/index.html
• https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_freespace_segmentation/index.html
• https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_dnn_stereo_depth/index.html