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This paper aims to report a novel practical algorithm for manipulation planning of multiple articulated robots.

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.

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.

The reported research has been developed for task‐oriented applications with prior knowledge. Future work will focus on acquiring prior knowledge using vision systems.

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.

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.

In response to the poor reliability of live maintenance robots in semi-structured environments and the difficulty of monitoring their operation status, this paper aims to propose an online method for evaluating the operation status of high-voltage live maintenance robots based on fuzzy control.

The robot bolt tightening operation is taken as an example. During the whole operation process, the key technologies of bolt tightening are analyzed theoretically, a two-dimensional fuzzy control model of bolt tightening process control is established and the control parameters, which characterize the operation status, are obtained. Through dynamic adjustment of the fuzzy controller, real-time online monitoring of the robot operation status can be achieved.

The results of simulation experiments and 220 kV live operation experiments show that the reliability of robot bolt tightening is greatly enhanced by the proposed control method.

The results not only verify the engineering practicability of the fuzzy control-based method but also indicate that it can improve efficiency, safety and operability.