查看更多>>摘要：Reporters obtained the following quote from the background information supplied by the inventors:“For autonomous or semi-autonomous robotic devices to operate autonomously or with minimal inputand/or external control within an environment , methods for mapping the environment are helpful suchthat the robotic device m ay autonomously remain and operate within the environment. Methods formapping a n environment have been previously proposed. For example, the collection and sto rage of alarge amount of feature points from captured images of an environment wherein recognizable landmarksamong the data may be identified and matched for building and updating a map has been proposed. Suchmethods can require signific ant processing power and memory due to the large amount of feature points extrac ted from the captured images, their storage and sophisticated techniques used in creating the map.For example, some methods employ an EKF technique where the p ose of the robotic device and theposition of features within the map of the env ironment are estimated and stored in a complete statevector while uncertainties in the estimates are stored in an error covariance matrix. The main drawback isthe computational power required to process a large number of features having l arge total state vector andcovariance matrix. Further, methods employing EKF ca n require accurate measurement noise covariancematrices a priori as inaccurate sensor statistics can lead to poor performance. Other methods of mappingan envi ronment use a distance sensor of the robotic device to measure distances from th e distancesensor to objects within the environment while tracking the position of the robotic device. For example,a method has been proposed for constructing a map of the environment by rotating a distance sensor360-degrees at a measured rotational velocity while taking distance measurements to objects within the environment. While this method is simple, the method is limited as the mapping pro cess of the environmentrelies on the distance sensor initially rotating 360-deg rees. If the distance sensor is installed on a roboticdevice, for example, the robotic device may rotate 360-degrees initially to finish mapping the environment before performing work. Another similar method provides that the robotic devic e may immediatelytranslate and rotate while measuring distances to objects, all owing it perform work while simultaneouslymapping. The method however uses EKF SLAM approach requiring significant processing power. Somemapping methods descr ibe the construction of an occupancy map, where all points in the environment are tracked, including perimeters, empty spaces, and spaces beyond perimeters, and assigned a status, suchas “occupied,” “unoccupied,” or “unknown.” This approac h can have high computational costs. Othermethods require the use of additional components for mapping, such as beacons, which must be placedwithin the enviro nment. This is undesirable as additional components increase costs, take up spac e, andare unappealing to have within, for example, a consumer home.
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