Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142110
Title: Heterogeneous multi-robot mission planning for coordinated tasks execution
Authors: Dwiyasa, Felis
Lim, Meng-Hiot
Kang, Pyo
Foo, Ren-Xiang
Teo, Jason Shi-Wei
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Dwiyasa, F., Lim, M.-H., Kang, P., Foo, R.-X., & Teo, J. S.-W. (2020). Heterogeneous multi-robot mission planning for coordinated tasks execution. Proceedings of Soft Computing for Problem Solving 2019, 1139, 167-173. doi:10.1007/978-981-15-3287-0_13
Conference: 9th International Conference on Soft Computing for Problem Solving (SocProS 2019)
Abstract: The use of robotics and autonomous systems to perform various missions has become increasingly popular and widely accepted. The scope of missions that can be performed by such systems includes complex tasks that require coordination and cooperation between multiple robots, not just simple repetitive tasks. Mission planner plays a vital role in making sure that the tasks performed by the robots are conducted in an efficient manner and meet all the mission requirements. In designing a mission planner, it is crucial to consider not only the functional aspect of the system but also its modularity, scalability, and interoperability. In this paper, we proposed an architecture of a heterogeneous multi-robot mission planner system that is based on robotic operating system (ROS). The system is designed to support heterogeneous multi-robot, where there are several types of robots having unique sets of capabilities and properties, which contributes greatly to the complexity of the mission planner.
URI: https://hdl.handle.net/10356/142110
ISBN: 978-981-15-3286-3
DOI: 10.1007/978-981-15-3287-0_13
Schools: School of Electrical and Electronic Engineering 
Organisations: National Research Foundation (NRF) Singapore
Rights: © 2020 Springer Nature Singapore Pte Ltd. All rights reserved. This paper was published in Proceedings of Soft Computing for Problem Solving 2019 and is made available with permission of Springer Nature Singapore Pte Ltd.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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