A Rigid Body Consensus-Based Collaborative Control Framework for Dual AGVs in Smart Port

Abstract

To address issues with Automated Guided Vehicles (AGVs) in ports, such as low utilization, poor flexibility, and weak adaptability, this paper presents a new collaborative transport solution. This solution enables the virtual connection of two AGVs via the Internet of Things (IoT) without physical connections. A hybrid collaborative control framework is designed to implement this solution, integrating feedback and feed-forward control. Within this framework, the transport AGV and container are treated as a single rigid body. A hierarchical decoupling approach is applied to separately design lateral and longitudinal feedback controllers for the leader AGV. Additionally, a centralized feed-forward controller for the follower AGV is developed based on rigid-body consensus theory and the AGV’s kinematic model. Typical port transportation conditions are established on both a high-fidelity dynamics software platform and a self-developed port platform using real-world port data. Tests with two AGVs show a distance error of 0.019 m and an angle error of 0.2∘ at handling points, meeting port operational metrics. These results demonstrate the scheme’s effectiveness in addressing gaps in research on nonholonomic constraint robots in collaborative transport, offering solutions for scenarios with multiple constraints and high precision requirements. Importantly, this work provides insights for developing IoT-enabled smart ports.