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|dc.description.abstract||Most range-only simultaneous localization and mapping (RO-SLAM) algorithms have considered direct measurements between robot and its neighbor nodes only, even though other inter-node measurements can be actively used to improve the performance. In addition, most of them assume nodes are static, i.e., fixed on one place and cannot be applied to dynamic environments where some or all of nodes are moving. To address the aforementioned issues, a cooperative dynamic RO-SLAM (CDRO-SLAM) is proposed in this paper, which is a RO-SLAM algorithm based on sum of Gaussian (SoG) filter with cooperative measurements in dynamic environments. The proposed CDRO-SLAM integrates all the inter-node measurements for localization, which results in a smaller map estimation error with a faster convergence speed than the conventional ROSLAM. Moreover, the proposed CDRO-SLAM can also track movement of any nodes under the dynamic environment by resetting and updating the SoG variables. Such advantages of the proposed CDRO-SLAM algorithm are verified with the real experimental data.||-|
|dc.publisher||2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)||-|
|dc.subject||Sum of Gaussian||-|
|dc.title||Cooperative Range-only SLAM based on Sum of Gaussian Filter in Dynamic Environments||-|
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