Multi-robot path planning is one of the most attractive issues in the field of multiple robots. Compared with the algorithm for the single-robot path planning

the problem of multi-robot path planning

which takes obstacle avoidance and cooperation into account simultaneously

is more difficult and complex. Hence

a novel improved rapidly-exploring random tree algorithm for multi-robot formation path planning in this paper is proposed to address these obstacle avoidance and cooperation problems. The constraint condition of positional relationship is defined by modeling the multi-robot formation shape. Besides

the heading of formation is adjusted with the direction the exploring tree expands. Additionally

simulations are conducted for two different models of robots: the particle model and the non-holonomic constraint dynamic model. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm.