Updating active x

From a SLAM perspective, these may be viewed as location sensors whose likelihoods are so sharp that they completely dominate the inference.However GPS sensors may go down entirely or in performance on occasions, especially during times of military conflict which are of particular interest to some robotics applications.The webinar will illustrate common failure modes, discuss the pros and cons of various types of testing technology, and help viewers create a plan that wil...

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Most practical SLAM tasks fall somewhere between these visual and tactile extremes.

Sensor models divide broadly into landmark-based and raw-data approaches.

Like many inference problems, the solutions to inferring the two variables together can be found, to a local optimum solution, by alternating updates of the two beliefs in a form of EM algorithm.

Statistical techniques used to approximate the above equations include Kalman filters, particle filters (aka.

At one extreme, laser scans or visual features provide details of a great many points within an area, sometimes rendering SLAM inference unnecessary because shapes in these point clouds can be easily and unambiguously aligned at each step via image registration.

At the opposite extreme, tactile sensors are extremely sparse as they contain only information about points very close to the agent, so they require strong prior models to compensate in purely tactile SLAM.Location-tagged visual data such as Google's Street View may also be used as part of maps.Essentially such systems simplify the SLAM problem to a simpler localisation only task, perhaps allowing for moving objects such as cars and people only to be updated in the map at runtime.Landmarks are uniquely identifiable objects in the world whose location can be estimated by a sensor—such as wifi access points or radio beacons.Raw-data approaches make no assumption that landmarks can be identified, and instead model directly as a function of the location.SLAM algorithms are tailored to the available resources, hence not aimed at perfection, but at operational compliance.

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