Task Allocation and Collaborative Planning Algorithm of the Sub-mother Unmanned Platform under Multi-task Constraints

In multi-robot systems, task allocation and collaborative planning can become less efficient and less successful as the number of tasks and the complexity of the target map increase. These challenges can even lead to search failures. To address these issues, this paper proposes a novel approach that employs a region segmentation algorithm to divide the task space into sub-regions. Subsequently, task allocation and collaborative planning are performed within each sub-region. The approach utilizes a sub-mother car unmanned platform, where the mother car is responsible for carrying and charging the sub-cars. The sub-cars, in turn, carry out the assigned tasks. Comparative experiments with the traditional ECBS-TA algorithm demonstrate the effectiveness of the proposed method. It improves the success rate, reduces runtime, and extends the applicability of the traditional ECBS-TA algorithm to large maps and environments with complex obstacles.