This work considers real-time continuous curvature (CC) path planning for car-like robots. It is motivated by the fact that Reeds-Shepp's (RS) based path planning remains unmatched in terms of computation efficiency and reliability when compared with various CC path planning results. Similar to , this paper post-processes RS paths to enforce the CC property, while ensuring CC paths contained in a neighborhood of the RS paths to maintain obstacle clearance. Targeting to alleviate concerns about reliability and computational efficiency, we exploit the geometric insights casted by Âµ tangency conditions  to post-process RS paths. Specifically, distinctive postprocessing scheme is devised offline for each type of discontinuous curvature junctions. The proposed schemes, though suboptimal, are straightforward, and result in CC path planning with guaranteed completeness at the negligible increase of computation. Effectiveness of proposed schemes and resultant algorithms is validated by numerical simulations.