In order to solve the problem of path planning in the unknown environment of mobile robots, a path-planning algorithm of rapidly-exploring random trees(RRT) based on subtarget search is proposed. On the one hand, aiming at the blind search problem inherent in the traditional RRT algorithm, the objective guidance function is introduced to form a goal-directed RRT path planning algorithm, which can decrease redundant search, and improve the efficiency of path planning. On the other hand, in order to enable the robot to reach the target point successfully when it firstly explores the unknown environment, three sub-target search strategies under different circumstances are proposed, which include the direct strategy in the barrier-free environment, the shortest distance strategy when the boundary point is swept, and the backward strategy when the boundary point is not swept. They make the robot can complete exploration of the unknown environment, and, more importantly, can overcome the local minimum point of the problem. Simulation results verify the feasibility and effectiveness of the proposed algorithm.