In an environment with limited space and dense goal configuration, the path of robot team is forced to coincide without much adjustment space, which is a challenge for multi-robot collaborative path planning. In this work, a novel Optimal Path and Timetable Planning (OPTP) method is proposed. The OPTP firstly generates the near-shortest paths for each robot by an RRT*-based planner. Then the timetables for each robot in the path-time space are created by the improved Particle Swarm Optimization (PSO) method. A heuristic bias is added to the PSO optimizer to efficiently mediate the conflict near the goal configuration. The OPTP achieves the near-shortest moving distance of the multi-robot team, as well as the near-optimal navigation makespan in face of complex obstacles, narrow channels, and dense goal configurations. The compared simulations and real-world experiments verify the effectiveness of the OPTP method.