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2005 DARPA Grand Challenge winner Stanley performed SLAM as part of its autonomous driving system. A map generated by a SLAM Robot. 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.
Point set registration is the process of aligning two point sets. Here, the blue fish is being registered to the red fish. In computer vision, pattern recognition, and robotics, point-set registration, also known as point-cloud registration or scan matching, is the process of finding a spatial transformation (e.g., scaling, rotation and translation) that aligns two point clouds.
Map learning cannot be separated from the localization process, and a difficulty arises when errors in localization are incorporated into the map. This problem is commonly referred to as Simultaneous localization and mapping (SLAM).
The optical flow vector of a moving object in a video sequence. In robotics and computer vision, visual odometry is the process of determining the position and orientation of a robot by analyzing the associated camera images.
Robot localization denotes the robot's ability to establish its own position and orientation within the frame of reference. Path planning is effectively an extension of localization, in that it requires the determination of the robot's current position and a position of a goal location, both within the same frame of reference or coordinates.
Map matching is the problem of how to match recorded geographic coordinates to a logical model of the real world, typically using some form of Geographic Information System. The most common approach is to take recorded, serial location points (e.g. from GPS ) and relate them to edges in an existing street graph (network), usually in a sorted ...
Geopositioning can be referred to both global positioning and outdoor positioning, using for example GPS, and to indoor positioning, for all the situations where satellite GPS is not a viable option and the localization process has to happen indoors. For indoor positioning, tracking and localization there are many technologies that can be used ...
For localization, at least three known reference locations are necessary to localize. Several localization algorithms based on Sequential Monte Carlo (SMC) method have been proposed in literature. [2] [3] Sometimes a node at some places receives only two known locations and hence it becomes impossible to localize. To overcome this problem, dead ...