公开(公告)号：US20200182622A1

公开(公告)日：2020-06-11

申请号：US16213553

申请日：2018-12-07

Applicant: Zebra Technologies Corporation

Inventor： Sadegh Tajeddin ,  Harsoveet Singh ,  Jingxing Qian

IPC: G01C21/20 ,  G05D1/02 ,  G06Q50/28

Abstract: A method for localization of a mobile automation apparatus includes, at a navigational controller: generating a set of candidate poses within an environmental map; updating the candidate poses according to motion data corresponding to movement of the mobile automation apparatus; receiving observational data collected at an actual pose of the mobile automation apparatus; generating (i) respective weights for the candidate poses, each weight indicating a likelihood that the corresponding candidate pose matches the actual pose, and (ii) a localization confidence level based on the weights; responsive to determining whether the localization confidence level exceeds a candidate pose resampling threshold: when the determination is affirmative, (i) increasing the candidate pose resampling threshold and (ii) generating a further set of candidate poses; and when the determination is negative, (i) decreasing the candidate pose resampling threshold without generating the further set; and repeating the updating, the receiving, the generating and the determining.

公开(公告)号：US11079240B2

公开(公告)日：2021-08-03

申请号：US16213553

申请日：2018-12-07

Applicant: Zebra Technologies Corporation

Inventor： Sadegh Tajeddin ,  Harsoveet Singh ,  Jingxing Qian

IPC: G01C21/20 ,  G06Q50/28 ,  G05D1/02

Abstract: A method for localization of a mobile automation apparatus includes, at a navigational controller: generating a set of candidate poses within an environmental map; updating the candidate poses according to motion data corresponding to movement of the mobile automation apparatus; receiving observational data collected at an actual pose of the mobile automation apparatus; generating (i) respective weights for the candidate poses, each weight indicating a likelihood that the corresponding candidate pose matches the actual pose, and (ii) a localization confidence level based on the weights; responsive to determining whether the localization confidence level exceeds a candidate pose resampling threshold: when the determination is affirmative, (i) increasing the candidate pose resampling threshold and (ii) generating a further set of candidate poses; and when the determination is negative, (i) decreasing the candidate pose resampling threshold without generating the further set; and repeating the updating, the receiving, the generating and the determining.