Purpose – This paper aims to report a novel practical algorithm for manipulation planning of multiple articulated robots. Design/methodology/approach – This paper proposes a model-based approach to distributing trajectory segments to individual robots in a multirobot system, given a task in terms of trajectories. This approach consists of three modules: task trajectory generation, cooperative robots selection, and joint trajectory generation. Findings – The proposed algorithm has been implemented into a simulation system with four-planar robots and a multirobot-packing system, which has shown the effectiveness of the presented method. It improves the flexibility of robot cooperation and handles dynamically cooperative trajectories by using a modularized mapping from Cartesian space to joint space of robots. Research limitations/implications – The reported research has been developed for task-oriented applications with prior knowledge. Future work will focus on acquiring prior knowledge using vision systems. Practical implications – The key contribution of this paper is that it offers a practical real-time solution to task-oriented applications. For instance, the proposed method could close the gaps and significantly improve work efficiency in carton packing involved in industrial chains. Originality / value – The reported work allows a multirobot system realtime, dynamically distributing trajectory segments to individual robots for task-oriented applications. Industrial practitioners would benefit from employing it in their existing systems, e.g. the car assembly industry.