Learning to select useful landmarks

Learning to Select Useful Landmarks

Learning to Select Useful Landmarks

To navigate effectively, an autonomous agent must be able to quickly and accurately determine its current location. Given an initial estimate of its position (perhaps based on dead-reckoning) and an image taken of a known environment, our agent first attempts to locate a set of landmarks (real-world objects at known locations), then uses their angular separation to obtain an improved estimate o...

Learning to Select Useful

To navigate eeectively, an autonomous agent must be able to quickly and accurately determine its current location. Given an initial estimate of its position (perhaps based on dead-reckoning) and an image taken of a known environment, our agent rst attempts to locate a set of landmarks (real-world objects at known locations), then uses their angular separation to obtain an improved estimate of i...

Learning to select distinctive landmarks for mobile robot navigation

In landmark-based navigation systems for mobile robots, sensory perceptions (e.g., laser or sonar scans) are used to identify the robot’s current location or to construct internal representations, maps, of the robot’s environment. Being based on an external frame of reference (which is not subject to incorrigible drift errors such as those occurring in odometry-based systems), landmark-based ro...

Learning to Autonomously Select Landmarks for Navigation and Communication

Selecting landmarks for use by a navigating mobile robot is important for map-building systems. However, it can also provide a way by which robots can communicate route information, so that one robot can tell another how to find a goal location. A route through an environment can be described by the landmarks encountered along the path, and a robot following the same path must identify the perc...