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Range-Aided Drift-Free Cooperative Localization and Consistent Reconstruction of Multi-Ground Robots

Haifeng Zhang, Zhitian Li, Shuaikang Zheng, Pengcheng Zheng, Xingdong Liang, Yanlei Li, Xiangxi Bu, Xudong Zou

发表年份
2023
引用次数
9

摘要

Fast and flexible dense reconstruction has been extensively studied due to its wide application. Considering the efficiency of multi-robot systems, cooperative reconstruction is gaining attention. Classic methods rely on inter-robot loop closures, which cannot work when there is no common area between robots. Ultra-wideband sensors provide distance measurement and can replace loop closures in multi-robot systems. However, ranging-based schemes do not solve the inconsistency of reconstruction, which is caused by odometry drift. We propose a range-aided cooperative localization and consistent reconstruction system. First, the system's front end tightly couples visual odometry and ranging to perform loop-independent cooperative reconstruction and reduce odometry drift. Second, the back end detects overlapping regions in submaps and proposes a novel dense pose graph optimization (PGO) step to further eliminate all trajectory drift and achieve consistent reconstruction. Extensive field experiments demonstrate the effectiveness and high performance of the system.

关键词

OdometryVisual odometryRobotComputer scienceRangingArtificial intelligenceComputer visionTrajectoryRange (aeronautics)Mobile robot

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