PLC-Based Trajectory Control of an Omnidirectional Mecanum-Wheel AGV Using Visual–Inertial Tracking and Grid-Based A* Path Planning - Binh-Hau Nguyen; Hang-Ri Nguyen; Phuoc-Duy Nguyen; Trung-Kien Pham; Dang-Khoa Tran; Quoc-Trung Nguyen; Tu-Duc Nguyen; Thi-Ngoc-Thao Nguyen; Thi-Ngoc-Hieu Phu; Hoang-Lam Le; Hoang-Phuc Le; Cong-Tan Bien (Control Systems and Optimization Letters, 2026)
This paper presents a PLC-based omnidirectional Automated Guided Vehicle (AGV) using four Mecanum wheels for indoor material transportation. The system integrates a Mitsubishi Q-series PLC for motion execution, an Intel RealSense T265 visual–inertial camera for relative pose tracking, and a Python-based supervisory interface running on a laptop. The AGV operates in a known static workspace represented by a predefined grid map, where each cell corresponds to 0.1 m in the real environment. Static obstacles, pickup points, and drop-off points are manually defined before operation. The A* algorithm generates collision-free waypoint paths, which are converted into wheel velocity commands through the inverse kinematic model and transmitted to the PLC via Ethernet-based MC-Protocol. Experimental tests at a commanded speed of 0.2 m/s show that the prototype can perform eight-directional motion and complete predefined pickup–delivery tasks. The main limitations include tracking drift of the T265 camera, lighting sensitivity, wheel slippage on tiled floors, and communication latency. Future work will focus on sensor fusion, real-time obstacle detection, and fail-safe mechanisms.