Translocation is an important class of structural variants known to be associated with cancer formation and treatment. The recent development in single-molecule sequencing technologies that produce long reads has promised an advance in detecting translocations accurately. However, existing tools struggled with the high base error-rate of the long reads. Figuring out the correct translocation breakpoints is especially challenging due to suboptimally aligned reads. To address the problem, we developed Translocator, a robust and accurate translocation detection method that implements an effective realignment algorithm to recover the correct alignments. For benchmarking, we analyzed using NA12878 long reads against a modified GRCh38 reference genome embedded with translocations at known locations. Our results show that Translocator significantly outperformed other state-of-The-Art methods, including Sniffles and PBSV. On Oxford Nanopore data, the recall improved from 48.2% to 87.5% and the precision from 88.7% to 92.7%. Translocator is available open-source at https://github.com/HKU-BAL/Translocator.