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This paper presents a method for obstacle avoidance path planning specifically designed for tractor–trailer system. A collision prevention constraint for both the tractor and trailer was established through kinematic analysis within the path planning algorithm. An evaluation method for obstacle avoidance was proposed, which determines whether the vertices of the tractor–trailer outline lie outside the obstacle polygon. The adaptive homotopy algorithm is employed to facilitate nonlinear path planning for the tractor implements. A simulation model for obstacle avoidance path planning was developed using MATLAB and AMPL software for the JM204 tractor and trailer. In the simulation experiments, two distinct working conditions were created based on the distance between the initial position of the tractor–trailer and the obstacles. The results of the simulation experiments demonstrate that the tractor–trailer system can successfully avoid obstacles and reach the target position via the planned path under different working conditions. As the distance between the tractor–trailer unit and the obstacle decreases, the number of iterations and the computational load increase. The simulation results validate the effectiveness of the proposed obstacle avoidance path planning method for the tractor–trailer system.

Driving a vehicle with a passive trailer has been the subject of numerous studies. Current control strategies are mostly used by differential geometry, linear algebra, fuzzy regulators, and artificial neural networks. The objective of this study is to design an algorithm for autonomous control of the tractor-trailer system reversing based on an algorithm using a PSD controller and to verify it on a simulated mathematical model. All parameters listed in the models and experiments are performed based on the existing tractor-trailer system. Dynamic models of steering and velocity control were identified and incorporated into the simulation. Result includes a stable operation of the steering without oscillating. The proposed algorithm can be implemented in microcontrollers without the need for high computing power.

Autonomous tractor–trailer robots possess a broad spectrum of applications but pose significant challenges in control due to their nonlinear and underactuated dynamics. Unlike the tractor, the motion of the trailer cannot be directly actuated, which often results in a deviation from the intended path. In this study, we introduce a novel method for generating and following trajectories that circumvent obstacles, tailored for a tractor–trailer robotic system constrained by multiple factors. Firstly, leveraging the state information of both the obstacles and the desired trajectory, we formulate an improved trajectory for obstacle avoidance using the nonlinear least squares method. Subsequently, we propose an innovative tracking controller that integrates a universal barrier function with a state transformation strategy. This amalgamation facilitates the accurate tracking of the prescribed trajectory. Our theoretical analysis substantiates that the proposed control methodology ensures exponential convergence of the line-of-sight (LOS) distance and angle tracking errors, while enhancing the transient performance. To validate the efficacy of our approach, we present a series of simulation results, which demonstrate the applicability of the developed control strategy in managing the complex dynamics of tractor–trailer robots.

Tractor-trailer units are the primary horizontal transport medium between the ship and the stacking area in container ports, and their efficient operation has a strong influence on loading and unloading rates. This paper presents a comparative study of the vessel loading and unloading procedure at the Port of Durban for conventional tractor-trailer units versus short multi-trailer systems. A discrete event simulation approach was used to model the terminal's operations using the two types of vehicles, and to analyse the effect on the terminal's performance and operating costs. The results of the study showed that the current fleet of tractor-trailer units can be replaced by a fleet of multi-trailer systems capable of carrying four twenty-foot equivalent units (TeUs) each, resulting in equivalent quay crane productivity while reducing the terminal's operating cost per shift for the horizontal transport subsystem.

In this paper, a dynamic automatic obstacle avoidance trajectory planning and tracking control framework is proposed for tractor-trailer system. Tractor-trailer is a special class of multibody and nonholonomic system, whose backward and forward operations have difference kinetic mechanisms. Because the obstacle avoidance behaviors are concerned with the two motion modes, the kinematic models including backward and forward movements are firstly derived. Secondly, a time-based quintic polynomial function is developed to plan two kinds of dynamic obstacle avoidance trajectories based on dynamics constraints and the information from on board sensors, so as to minimize the collision risk. Thirdly, a model predictive control (MPC)-based posture controller is designed, by which better tracking performance can be achieved for both forward and backward obstacle avoidance maneuvers. Lastly, the simulation results validate the effectiveness of the proposed dynamic obstacle avoidance framework and the designed methods.

Safety is a fundamental issue in autonomous mobile robot design. This paper presents a safety-critical control framework for nonholonomic tractor-trailer vehicles subject to both safety and physical constraints. Control barrier functions (CBFs) are employed to enforce hard safety constraints, generating a safe set that ensures obstacle avoidance. These CBFs are integrated with control Lyapunov functions (CLFs) to enable trajectory tracking while maintaining safety. To reduce conflicts between CBFs and CLFs and improve obstacle avoidance performance, we optimize their decay rates. Leveraging the concept of differential flatness, we design a controller that enables the system to follow the desired safe trajectory. Finally, the effectiveness and performance of the proposed method are demonstrated through numerical simulations and real-world experiments.

The design and industrial innovation of intelligent agricultural machinery and equipment for saline alkali land are important means for comprehensive management and capacity improvement of saline alkali land. The autonomous and unmanned agricultural tractor is the inevitable trend of the development of intelligent machinery and equipment in saline alkali land. As an underactuated system with non-holonomic constraints, the independent trajectory planning and lateral stability control of the tractor-trailer system (TTS) face challenges in saline alkali land. In this study, based on the nonlinear underactuation characteristics of the TTS and the law of passive trailer steering, a dual-trajectory collaborative control model was designed. By solving the TTS kinematic/dynamic state space, a nonlinear leading system that can generate the reference pose of a tractor-trailer was constructed. Based on the intrinsic property of the lateral deviation of the TTS, a collaborative trajectory prediction algorithm that satisfies the time domain and system constraints is proposed. Combining the dual-trajectory independent offset and lateral stability parameter of the TTS, an energy function optimization control parameter was constructed to balance the system trajectory tracking performance and lateral control stability. The experimental results showed good agreement between the predicted trailer trajectory and the collaborative control trajectory, with an average lateral error not exceeding 0.1 m and an average course angle error not exceeding 0.054 rad. This ensures that the dynamic controller designed around the tractor-trailer underactuation system can guarantee the smoothness of the trailer trajectory and the controlling stability of the tractor in saline alkali land.

Single axle trailers are most common means of transportation in rural areas. For maintaining stability of tractor-trailer system, it is necessary to ascertain different factors and forces which disturb equilibrium during transportation. The effect of operating conditions and design parameters of single axle trailers on its stability were analysed using scaled physical model under static conditions. Static load tests on varying slopes were carried out using scaled physical model to determine the variation in load pattern on the trailer tyre and its hitch point. The angle of inclination along with the normal load influenced the load shift from outer wheel to inner wheel, causing instability of the tractor-trailer system. The axle position had a paramount effect on vertical hitch load. Hitch length and axle position were two major design considerations that ensured proper distribution of normal load. A normal load less than 4273 N, and the centre axle position of trailer was safe operating conditions for tractor-trailer system at lateral slope (angle of inclination) of less than 15 degrees.

Trajectory tracking is one of the main control problems in the context of Wheeled Mobile Robots (WMRs). Control of underactuated systems has been focused by many researchers during past few years. In this paper, tracking control of a Tractor–Trailer Wheeled Mobile Robot (TTWMR) has been discussed. TTWMR includes a differential drive WMR towing a passive spherical wheeled trailer. Spherical wheels in contrast with standard wheels make the robot highly underactuated with severe non-linearities. Underactuation is due to the use of spherical wheeled trailer to increase robots' maneuverability and degrees of freedom. In fact, standard wheels are subjected to non-holonomic constraints due to pure rolling and non-slip conditions, which reduce robot maneuverability. In this paper, after introducing the robot, kinematics and kinetics models are obtained. Then, based on a physical intuition, a novel control algorithm is developed for the robot, i.e. Lyapunov-PID control algorithm. Subsequently, singularity avoidance of the proposed algorithm is discussed and the stability of the algorithm is analyzed. Finally, simulation and experimental results are presented which reveal the effectiveness of the proposed algorithm.

The purpose of this paper is to design a stabilizing controller for a car with n connected trailers. The proposed control algorithm is constructed on the Lyapunov theory. In this paper, the purpose of navigating the system toward the desired point considering the slip phenomenon as a main source of uncertainty is analyzed. First mathematical models are presented. Then, a stabilizing control approach based on the Lyapunov theory is presented. Subsequently, an uncertainty estimator is taken into account to overcome the wheel slip effects. Obtained results show the convergence properties of the proposed control algorithm against the slip phenomenon.