Collaboration of Multiple Autonomous Industrial Robots through Optimal Base Placements



Multiple autonomous industrial robots can be of great use in manufacturing applications, particularly if the environment is unstructured and custom manufacturing is required. Autonomous robots that are equipped with manipulators can collaborate to carry out manufacturing tasks such as surface preparation by means of grit-blasting, surface coating or spray painting, all of which require complete surface coverage. However, as part of the collaboration process, appropriate base placements relative to the environment and the target object need to be determined by the robots. The problem of finding appropriate base placements is further complicated when the object under consideration is large and has a complex geometric shape, and thus the robots need to operate from a number of base placements in order to obtain complete coverage of the entire object. To address this problem, an approach for Optimization of Multiple Base Placements (OMBP) for each robot is proposed in this paper. The approach aims to optimize base placements for multi-robot collaboration by taking into account task-specific objectives such as makespan, fair workload division amongst the robots, and coverage percentage; and manipulator-related objectives such as torque and manipulability measure. In addition, the constraint of robots maintaining an appropriate distance between each other and relative to the environment is taken into account. Simulated and real-world experiments are carried out to demonstrate the effectiveness of the approach and to verify that the simulated results are accurate and reliable.


Autonomous industrial robots Base placement optimization Complete coverage Multi-robot collaboration 

Mathematics Subject Classification (2010)

68T40 65K99 


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This research is supported by SABRE Autonomous Solutions Pty Ltd and the Centre for Autonomous Systems (CAS) at the University of Technology Sydney, Australia. A special thank to Dr. Andrew Wing Keung To for his feedback and assisting with various aspects of the experiments. Authors also thank Prof. Gamini Dissanayake, Assoc. Prof. Shoudong Huang, Mr. Teng Zhang and Mr. Raphael Falque for their valuable recommendations and discussions.


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© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Centre for Autonomous Systems (CAS) at the University of Technology Sydney (UTS)UltimoAustralia

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