Method and device for displacement computing and method and device for simultaneous localization and mapping

Abstract

The invention discloses a method and a device for simultaneous localization and mapping (SLAM). A method for displacement computing comprises the steps of repeatedly acquiring an acceleration vector alpha and a gesture vector beta of a movable object (such as a robot or a handheld device) based on a fixed time interval delta t, obtaining displacement of the object during the time interval delta t from time of t-delta t to time of t according to measured data and instantaneous speed V' (t-delta t) estimated in advance and obtaining a gesture vector beta (t) of the movable object during the time of t, wherein delta t = n*delta t, n belongs to N, estimating displacement according to data collected by a three-dimensional camera installed on the movable object and the gesture vector beta (t), carrying out filtering on the displacement delta D (t) to obtain delta D' (t), and then achieving construction of a three-dimensional map, updating the instantaneous speed V' (t) according to obtained delta D' (t) obtained through filtering, and using the instantaneous speed V' (t) for next synchronization displacement and mapping computing.

Description

technical field [0001] The invention relates to a displacement calculation method and equipment, and an instant positioning and map construction method and equipment. More specifically, it relates to a displacement calculation method and device capable of improving accuracy and processing speed, and an instant positioning and map construction method and device. Background technique [0002] Simultaneous Localization and Mapping (SLAM) is currently a hot research topic in robot localization. SLAM refers to the fact that the robot creates a map in a completely unknown environment under the condition that its own position is uncertain, and at the same time uses the map for autonomous positioning and navigation. The SLAM problem can be described as: the robot starts to move from an unknown position in an unknown environment, locates itself according to position estimation and sensor data during the movement, and builds an incremental map at the same time. Much progress has bee...

AI Technical Summary

Problems solved by technology

The disadvantages of this method are: firstly, such processing is very time-consuming due to the high computational load; in addition, the accuracy is not high; finally, the method is also limited by the background light, for example, in a darker background light case, the effect is not good

However, the disadvantages of this method are: firstly, the design and production of the electromechanical machine is very complicated and expensive; secondly, as the odometer of the electromechanical machine is used and ages, the stability decreases; Odometers are only suitable for 2D measurements and cannot be used for 3D measurements; finally, electromechanical odometers are expensive and complex to maintain

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