<P> In robotic mapping and navigation , simultaneous localization and mapping ( SLAM ) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent 's location within it . While this initially appears to be a chicken - and - egg problem there are several algorithms known for solving it , at least approximately , in tractable time for certain environments . Popular approximate solution methods include the particle filter , extended Kalman filter , and GraphSLAM . </P>
<P> In robotic mapping and navigation , simultaneous localization and mapping ( SLAM ) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent 's location within it . While this initially appears to be a chicken - and - egg problem there are several algorithms known for solving it , at least approximately , in tractable time for certain environments . Popular approximate solution methods include the particle filter , extended Kalman filter , and GraphSLAM . </P>
what does simultaneous localization and mapping ( slam ) software do ( select all that applies . )
what does simultaneous localization and mapping ( slam ) software do ( select all that applies . )
constructing or updating a map of an unknown environment while simultaneously keeping track of an agent 's location within it
constructing or updating a map of an unknown environment while simultaneously keeping track of an agent 's location within it