**6. Conclusions**

A UT-based CLAT method is proposed to realize multi-robot self-localization and target tracking in a distributed fashion. The proposed method is recursive, and only the most recent estimation is stored within each local robot. The communication is limited to the two robots within the relative measurement, and estimation consistency is guaranteed with the covariance split and covariance intersection method. To deal with the nonlinearity in the dynamics models and measurement models, a UT was integrated into the CLAT framework. Both simulation and experimental results show that the proposed method can fulfill the self-localization and target tracking task in practical multi-robot operation scenarios. Future works will focus on the theoretical analysis of the error bounds of both self-localization and target tracking on the basis of different measurement setups.

**Author Contributions:** Investigation, Y.L.; Methodology, Y.L.; Project administration, Q.P.; Software, J.L.; Supervision, Q.P.

**Funding:** This work is supported by the National Natural Science Foundation of China under Grant 61603303, 61473230, the Natural Science Foundation of Shaanxi Province under Grant 2017JQ6005, 2017JM6027, the China Postdoctoral Science Foundation under Grant 2017M610650 and the Fundamental Research Funds for the Central Universities under Grant 3102017JQ02011.

**Conflicts of Interest:** The authors declare no conflict of interest.

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