The installation process of numerous Bluetooth Low Energy (BLE) beacons in the indoor positioning environment usually requires the manual measurement of the beacon's physical coordinates which tends to be a labor-intensive process. In this work, we aim to create a BLE beacon map by obtaining their coordinates from in situ Received Signal Strength (RSS) observations on a smartphone in a short period of time. This paper proposes a method of automatic localization for twin BLE beacons based on Range-Only Simultaneous Localization and Mapping (RO-SLAM) approach and multi-hypothesis Extended Kalman Filter (EKF), on the condition that only the relative distance of twin beacons is known. In this method, a person holding a smartphone collects RSS of BLE beacons by walking around with no requirement of predefined trajectory. Normally, the lack of angular information on the sensor involves the difficulty of finding a good initial value of the state vector in the EKF, that requires substantial time to evolve the estimation enough. In our proposed method, tracking the multiple hypotheses which represent the probability distribution of possible locations of the BLE beacon and smartphone makes the results obtainable in a brief RSS survey. The hypotheses generation process employs the interval information of twin BLE beacons to reduce the number of hypotheses and consequently the computational load. The experimental evaluation using commercial off-the-shelf devices show that the proposed method offers a significant improvement in the time required to evolve the location estimation, while the use of twin BLE beacons can suppress the total number of hypotheses.