Multi-agent system for improved safety and productivity of earthwork equipment using real-timelocation systems Vahdatikhaki, Faridaddin; Hammad, Amin; Langari, Seied Mohammad
The growing complexity and scope of construction projects is making productivity and safety of earthwork of a great concern for project and site managers. In earthwork operations, where heavy machines are being used, various safety and risk issues put the timely completion of a project at stake. Additionally, the construction working environment is heavily susceptible to unforeseen changes and circumstances that could impact the project, both cost and schedule wise. As a response to the looming safety threats or unforeseen changes of working conditions, re-planning is almost always required. In order for re-planning to yield the optimum results, real-time information gathering and processing is a must. GPS and other Real-time Location Systems (RTLSs) have been used for the purpose of real-time data gathering and decision-making in recent years. Similarly, Location-based Guidance Systems (LGSs), e.g., Automated Machine Control/Guidance (AMC/G), are introduced and have been employed mainly for the purpose of high-precision earthwork operations. However, the current application of LGS is limited to the machine-level productivity optimization, which is not sufficient to address the project-level monitoring and decision-making needs. In the context of complex earthwork operations where several teams are concurrently working towards different ends, the globally optimized operations should coordinate the actions of multiple teams of equipment to eliminate the productivity lost by organizational, logistics and operational management. Therefore, the objective of this paper is to develop a Multi-agent System (MAS) structure to orchestrate the machine-level information (i.e. states and poses) induced based on RTLSs to a coherent project-level system committed to support operations towards the enhanced productivity and safety of the overall project. In the proposed MAS, several layers of agents are processing and managing the huge amount of collected sensory data into useful information that can be used in decision making at different operational levels. The proposed MAS has a semi-distributed structure to strike a balance between the optimality of the outputs and the required computational efforts. A case study is developed to demonstrate the applicability of the proposed MAS. Also, a two-layer safety mechanism is proposed based on which near real-time collision-free path planning and real-time collision avoidance can be performed. In the light of the results of the case study, it is found that the the proposed MAS structure is able to effectively address the team-level coordination of different pieces of equipment and improve the safety of construction site using the proposed two-layer safety mechanism.
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