- Survey SLAM algorithms across geometry-based and learning-based frameworks.
- Provide a unified formulation of the SLAM pipeline used across implementations.
- Classify and evaluate SLAM methods based on different environmental conditions.
- Survey SLAM algorithms across geometry-based and learning-based frameworks.
- Provide a unified formulation of the SLAM pipeline used across implementations.
- Classify and evaluate SLAM methods based on different environmental conditions.
SLAM algorithms face diverse environmental challenges:
- Dynamic elements in outdoor scenes 🌳
- Harsh imaging in underwater environments 🌊
- Blurriness in high-speed setups 🚗💨
Understanding these challenges is crucial for real-world applications.
SLAM algorithms face diverse environmental challenges:
- Dynamic elements in outdoor scenes 🌳
- Harsh imaging in underwater environments 🌊
- Blurriness in high-speed setups 🚗💨
Understanding these challenges is crucial for real-world applications.