Abstract
The collaborative control of the multi-agent system (MAS) marks the trend of intelligent transportation system (ITS). However, the collaborative control of MAS with flexible sampling periods remains a challenge, because under-driven systems are prone to random delays, data loss and sensor failures in semi-unstructured environment. Against the background of the semi-unstructured environment in a Dutch greenhouse, this paper puts forward a universal collaborative motion control algorithm for the MAS of automated guided vehicles (AGVs), in the light of the first-order dynamics of the system. The proposed algorithm is called continuous-step-rotate-run (CSRR). Besides, the enhanced depth image fusion positioning (EDIFP) scheme was designed to mitigate the disturbances on the control algorithm, arising from flexible sampling periods and data loss. To verify its effectiveness, the CSRR control algorithm was tested on an MAS of three under-driven BigPan AGVs. The results demonstrate that our algorithm can collaboratively control the AGVs in an effective and stable manner. The simple algorithm offers a desirable solution to the collaborative control of various MASs.
Highlights
Population aging and urbanization are two demographic trends shaping today’s world
Essential to intelligent transportation system (ITS), the automated guided vehicle (AGV)can effectively mitigate the risk of workers involved in dangerous operations [7], enhance the production efficiency, and ease the labor shortage induced by population aging [8]
The top view of the global coordinate system is presented in Figure 3, because this paper only considers the AGV control on the approximately 2D plane
Summary
Population aging and urbanization are two demographic trends shaping today’s world. Under these trends, the percentage of the labor force engaged in agriculture is falling, and the labor cost of agricultural workers is on the rise. The spraying operation could be implemented by an MAS of five small AGVs with a capacity of 100 L each, or a large, complex and costly AGV with a capacity of 500 L This calls for collaborative control of the MAS under semi-structured environment. Reference [30] preserved and coordinated the finitetime connectivity in a second-order MAS with limited sensing range, designed a distributed controller based on integral SMC and artificial potential field (APF), and proved that the controller achieves robust finite-time collaborative control, without sacrificing the connectivity of the communication network. Most of the existing studies only verify the theoretical results through simulation, rather than actual application or field testing Many of their control strategies only apply to a specific MAS, failing to support general applications. Reference [34] combined the APF and robust control technique into a formation control model, and estimated the unknown parameters in the model by an adaptive fuzzy logic algorithm
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