Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 37-45 |
| Number of pages | 9 |
| Journal | Industrial Robot: An International Journal |
| Volume | 35 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2008 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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