Aiming at the problem that standard iterative closest point（ICP） algorithm for simultaneous localization and mapping（SLAM） of mobile robots is complex and has high computational load

a SLAM method based on adaptive multi-feature matching is designed. The original scan point set is divided into blocks

and the matching strategy of ICP algorithm is improved by using the multi-feature information of blocks

which reduces the computational workload significantly and improves the speed of SLAM algorithm. The weighting coefficient of multi-feature information is adaptively adjusted to ensure the matching precision. Experimental results show that the adaptive multi-feature matching method reduces the computational workload and improves the matching precision.