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Parallel self-assembly is an efficient approach to accelerate the assemblyprocess for modular robots. However, these approaches cannot accommodatecomplicated environments with obstacles, which restricts their applications.This paper considers the surrounding stationary obstacles and proposes aparallel self-assembly planning algorithm named SAPOA. With this algorithm,modular robots can avoid immovable obstacles when performing docking actions,which adapts the parallel self-assembly process to complex scenes. To validatethe efficiency and scalability, we have designed 25 distinct grid maps withdifferent obstacle configurations to simulate the algorithm. From the resultscompared to the existing parallel self-assembly algorithms, our algorithm showsa significantly higher success rate, which is more than 80%. For verificationin real-world applications, a multi-agent hardware testbed system is developed.The algorithm is successfully deployed on four omnidirectional unmanned surfacevehicles, CuBoats. The navigation strategy that translates the discreteplanner, SAPOA, to the continuous controller on the CuBoats is presented. Thealgorithm's feasibility and flexibility were demonstrated through successfulself-assembly experiments on 5 maps with varying obstacle configurations.

Parallel Self-assembly for a Multi-USV System on Water Surface with Obstacles