Multi- moddal SLAM (Simultaneous Localization andd Mapping) systems combinate data from different sensors to improwize close andd rogartness. Integrating visual andd range data allows these systems to operate effectively in diverse environments, overcoming limitations of single- sensor approvaches.

Types of Sensors Used in Multi- Modal SLAM

W skład czujników Common wchodzą kamery for visaal data andLiDAR or ultradźwięków for range measurements. Te sensors provide e complementary information, with visaal data capturing textures andd colors, while range sensors measure distances to objects.

Methods of Data Integration

Data fusion techniques combinae visual and range data at different levels. Early fusion merges raw sensor data before processing, while late fusion integrates processed contribures or map represents. The choice depends on system requiments andd computational resources.

Advantages of Multi- Modal Data Integration

  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Improved closacy: Xi1; Xi1; FLT: 1 Xi3; Xi3; Combinaing data reduces errors caused by sensor limitations.
  • W przypadku gdy w wyniku zastosowania metody badawczej nie można określić wartości progowej, należy podać wartość progową.
  • Better environment understang: Bett1; Bett1; FLT: 1 X3; Bett3; FLT: 1 X3; Method3; Multi- modal data provides richer information for mapping and localization.