Dear Colleagues,

With the integration of mechanical, information, electronics, control, intelligence, and other interdisciplinary studies, industrial robotic applications are becoming increasingly complex in both theoretical and practical aspects. In particular, integrated collaborative robots, called multiple industrial robots (MIRs), include different typologies of robotic systems—e.g., multiple industrial manipulators, i.e., mobile robots with manipulators on board, or teams of autonomous vehicles, have been growing increasingly in various applications in recent years. The main motivation for employing MIRs is that they can be used to increase system effectiveness. In particular, with respect to a single autonomous robot or a team of noncooperating robots, MIRs can better perform a mission in terms of time and quality and can achieve tasks not executable by a single robot (e.g., moving a large object) or can take advantage of distributed sensing and actuation. A wider spatial area can also be covered more efficiently if more robots are deployed, and heterogeneous capabilities can be distributed across the team without having to dramatically change the payload (and thus price) of individual robots.

In response to advanced technology and application driving, several control and coordination strategies have already been developed for forming robots in order to collaboratively perform specific tasks using local interaction rules. The contributions to this Special Issue are expected to provide the latest results in collective analysis, estimation, optimization, coordinated control, and intelligent control of complex MIRs. Topics to be covered in this Special Issue include but are not limited to:

• Mathematical modeling of complex MIRs;
• Reduced modelling of large-scale MIRs;
• Coordinated control of heterogeneous MIRs;
• Decentralized control of MIRs;
• Analytical method of delay-coupled MIRs;
• MIRs with event-triggered computing;
• Estimation in MIRs;
• Partial synchronization of MIRs;
• Output regulation and optimization of MIRs;
• Fault diagnostics of MIRs;
• Safety and collision avoidance of MIRs;
• Intelligent control of MIRs.

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• robotic control
• decentralized control
• collective behaviors of complex networks
• output regulation
• intelligent control
• synchronization of heterogeneous robot networks
• fault diagnosis of robot systems.