Generalized task allocation and route planning for robots with multiple depots in indoor building environments

• Published in: Automation in construction Vol. 119; p. 103359
• Main Authors: Mantha, Bharadwaj R.K., Jung, Min Kyu, García de Soto, Borja, Menassa, Carol C., Kamat, Vineet R.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2020; Elsevier BV
• Subjects: Algorithms; Building service robots; Built environment; Facility management; Indoor environments; Logistics; Multiple robots; Optimization; Robots; Route planning; Service robots; Task allocation; Traveling salesman problem; Urban environments; Task allocation; Traveling salesman problem; Building service robots; Route planning; Built environment; Facility management; Optimization
• ISSN: 0926-5805; 1872-7891
• DOI: 10.1016/j.autcon.2020.103359

Recent advancements in sensing and robotic technologies facilitate the use of on-demand building service robots in the built environment. Multi-robot based systems have arguably more advantages when compared to fixed sensor-based and single-robot based systems. These task-oriented building service robots face several challenges, such as task-allocation and route-planning. Previous studies adopted approaches from other domains, such as outdoor logistics, and made application-specific assumptions. This study proposes a new methodology to optimize the task-allocation and route-planning for multiple indoor robots with multiple starts and destination depots where each robot begins and ends at the same depot (referred to as a fixed destination multi-depot multiple traveling salesman problem-fMmTSP). The performance of the proposed algorithm was compared with two existing outdoor-based algorithms. Results show that the proposed algorithm performs better in almost all the cases for the assumed network, which supports the need to develop algorithms specifically for indoor networks. •Focus of this paper is fixed destination multi-depot multiple traveling salesman (robots) problem for indoor networks.•A methodology is proposed to optimize the task allocation and route planning for building service robots.•Results are compared with outdoor network based algorithms such as genetic algorithm (GA) and k-means.•Results emphasize the need for indoor network based algorithms.•Proposed methodology can be generically applied to several building service robotic applications.