Research on Cooperative Trajectory Planning Algorithm Based on Tractor-Trailer Wheeled Robot

The tractor-trailer wheeled robot (TTWR) is a typical modular mobile robot system. It is widely used in industry and agriculture transportation because of its simple structure, heavy load, high efficiency, strong adaptability, and flexibility. Because it is a nonlinear and underactuated system subjected to nonholonomic constraints, the complexity of the system and influence of the inner wheel difference pose great challenges to its trajectory prediction and path planning. To solve this problem, this paper proposes a trajectory prediction algorithm for an unpowered trailer for the TTWR system. In contrast to traditional single-path planning, the algorithm combines the motion characteristics of the Ackermann chassis tractor, analyzes the trailer motion law, and fully considers the lateral deviation of the trailer during the turning process. The algorithm can plan a reasonable cooperative path for the TTWR system. To verify the feasibility and effectiveness of the algorithm, the algorithm is transplanted to the TTWR intelligent experimental platform. A comparison of the simulation and experimental results shows that under the control of the preview tracking algorithm, the maximum error between the actual trajectory of the trailer and the trajectory predicted by the algorithm is generally no more than 9 cm, and the average error is 3.7 cm. This algorithm can provide an effective basis for TTWR system trajectory planning and path tracking. This algorithm is of great significance to TTWRs in warehousing logistics, freight forwarding, and skidding transportation.