Design of obstacle avoidance controller for agricultural tractor based on ROS

The obstacle avoidance controller is a key autonomous component which involves the control of tractor system dynamics,such as the yaw lateral dynamics,the longitudinal dynamics,and nonlinear constraints including the speed and steering angles limits during the path-tracking process.To achieve the obstacle avoidance ability of control accuracy,an independent path re-planning controller is proposed based on ROS(Robot Operating System)nonlinear model prediction in this paper.In the design process,the obstacle avoidance function and an objective function are introduced.Based on these functions,the obstacle avoidance maneuvering performance is transformed into a nonlinear quadratic optimization problem with vehicle dynamic constraints.Moreover,the tractor dynamics maneuvering performance can be effectively adjusted through the proposed objective function.To validate the proposed algorithm,a ROS based tractor dynamics model and the SLAM(Simultaneous Localization and Mapping)are established for numerical simulations under different speed.The maximum obstacle avoidance deviation in the simulation is 0.242 m at 10 m/s,and 0.416 m at 30 m/s.The front-wheel rotation angle and lateral velocity are within the constraint range during the whole tracking process.The numerical results show that the designed controller can achieve the tractor obstacle avoidance ability with good accuracy under different conditions.

Trajectory tracking control of agricultural vehicles based on disturbance test

To improve the trajectory tracking robust stability of agricultural vehicles,a path tracking control method combined with the characteristics of agricultural vehicles and nonlinear model predictive control was presented.Through the proposed method,the path tracking problem can be divided into two problems with speed and steering angle constraints:the trajectory planning problem,and the trajectory tracking optimization problem.Firstly,the nonlinear kinematics model of the agricultural vehicle was discretized,then the derived model was inferred and regarded as the prediction function plant for the designed controller.Second,the objective function characterizing the tracking performance was put forward based on system variables and control inputs.Therefore,the objective function optimization problem,based on the proposed prediction equation plant,can be regarded as the nonlinear constrained optimization problem.What’s more,to enhance the robust stability of the system,a real-time feedback and rolling adjustment strategy was adopted to achieve optimal control.To validate the theoretical analysis before,the Matlab simulation was performed to investigate the path tracking performance.The simulation results show that the controller can realize effective trajectory tracking and possesses good robust stability.Meanwhile,the corresponding experiments were conducted.When the test vehicle tracked the reference track with a speed of 3 m/s,the maximum lateral deviation was 13.36 cm,and the maximum longitudinal deviation was 34.61 cm.When the added horizontal deviation disturbance Yr was less than 1.5 m,the controller could adjust the vehicle quickly to make the test car return to the reference track and continue to drive.Finally,to better highlight the controller proposed in this paper,a comparison experiment with a linear model predictive controller was performed.Compared to the conventional linear model predictive controller,the horizontal off-track distance reduced by 36.8%and the longitudinal deviation reduced by 32.98%when performing circular path tracking at a speed of 3 m/s.