<p>Multi-robot path planning in 3D environment is a complex and challenging task that needs to consider not only the high quality and safety of the paths, but also the coordination between robots. Aiming at this problem, a collaborative 3D path planning scheme using game theory and particle swarm optimization hybrid method (GTPHM) is presented in paper. Firstly, a cost function is formulated to transform path planning into an optimization problem, for which the multi-robot space motion equation is designed to satisfy the dynamic constraints. Then, a game theory-based multi-robot path planning framework is established, using collision costs and multi-objective heuristic functions as game gains to maintain the game-theoretic interaction between robots. In the improved particle swarm optimization algorithm (PSO), the particle space position transformation method designed according to the three-dimensional space vector, used as a strategy update mechanism based on game theory. For collisions avoidance between robots, each robot adjusts its cooperative strategy based on the behavior of the other robots. Each robot chooses the optimal cooperative strategy, and then gradually approaches the Nash equilibrium. Comparative experimental results show that GTPHM can effectively guide multi-robot to plan a safe and collision-free path from the starting point to the target point in mountain and city complex 3D environment.</p>