Design of obstacle avoidance controller for agricultural tractor based on ROS

Liu, Zhengduo; Zheng, Zhaoqin L�Wenxiu; Zhang, Wanzhi; Cheng, Xiangxun

doi:10.25165/j.ijabe.20191206.4907

Cited by 13 publications

(12 citation statements)

References 13 publications

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“…The relationship between the parameters of the Stanley controller is shown in Figure 5. The original steering command is shown in Equation (10) [17].…”

Section: Stanley Controller (St)mentioning

confidence: 99%

“…In recent years, navigation path tracking control of tractor navigation has been studied by many scholars, and several control algorithms have been proposed, mainly including geometric/kinematic control [1,2], PID control [3,4], fuzzy control [5][6][7], sliding mode control [8], model predictive control [9,10] and optimal control [11,12]. Pure pursuit is an algorithm based on geometric/kinematic control and is the most widely used agricultural machine path tracking algorithm because of its simplicity and efficiency [13,14].…”

Section: Introductionmentioning

confidence: 99%

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Path Tracking Control of an Autonomous Tractor Using Improved Stanley Controller Optimized with Multiple-Population Genetic Algorithm

et al. 2022

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To improve the path tracking accuracy of autonomous tractors in operation, an improved Stanley controller (IMP-ST) is proposed in this paper. The controller was applied to a two-wheel tractor dynamics model. The parameters of the IMP-ST were optimized by multiple-population genetic algorithm (MPGA) to obtain better tracking performance. The main purpose of this paper is to implement path tracking control on an autonomous tractor. Thus, it is significant to study this field because of smart agricultural development. According to the turning strategy of tractors in field operations, five working routes for tractors were designed, including straight, U, Ω, acute-angle and obtuse-angle routes. Simulation tests were conducted to verify the effectiveness of the proposed IMP-ST in tractor path tracking for all routes. The lateral root-mean-square (RMS) error of the IMP-ST was reduced by up to 36.84% and 48.61% compared to the extended Stanley controller and the original Stanley controller, respectively. The simulation results indicate that the IMP-ST performed well in guiding the tractor to follow all planned working routes. In particular, for the U and Ω routes, the two most common turning methods in tractor field operations, the path tracking performance of the IMP-ST was improved by 41.72% and 48.61% compared to the ST, respectively. Comparing and analyzing the e-Ψ and β-γ phase plane of the three controllers, the results indicate that the IMP-ST has the best control stability.

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“…The relationship between the parameters of the Stanley controller is shown in Figure 5. The original steering command is shown in Equation (10) [17].…”

Section: Stanley Controller (St)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Path Tracking Control of an Autonomous Tractor Using Improved Stanley Controller Optimized with Multiple-Population Genetic Algorithm

et al. 2022

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“…Unilateral brake steering has caused the existing crawler combine harvester to be inflexible in the field and prone to crawling and other issues. In order to resolve these problems, many scholars have carried out much research on soil properties, steering structure, ground viscosity resistance, steering control, etc [11][12][13] .…”

Section: Figure 1 Crawler Unilateral Brake Steering Status With 360°mentioning

confidence: 99%

Developments of crawler steering gearbox for combine harvester straight forward and steering in situ

Tang

Zhang

et al. 2020

International Journal of Agricultural and Biological Engineering

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Soil compaction and accumulation are caused by crawler steering. Soil characteristics would affect the ability of crawler straight forward and steering in situ. This paper studied the principle of straight forward steering and steering in situ mode of traditional unilateral brake steering gearbox of a crawler combine harvester. Then a positive and negative steering gearbox model was developed and processed. The performance of positive and negative steering gearbox was analyzed by performing two steering modes on soil compaction effect. Results showed that the positive and negative steering gearboxes can achieve three operating modes, such as straight forward, unilateral brake steering, and positive and negative steering in situ. The positive and negative steering in situ was smooth and without soil accumulation phenomenon. When the crawlers center distance, crawler grounding length, crawler width were 1150 mm, 1620 mm and 450 mm respectively, the rolling area and the scratch free area of positive and negative steering gearbox were 5.37 m 2 and 0.36 m 2 respectively. However, the rolling area and the scratch free area produced by unilateral brake steering gearbox were 13.92 m 2 and 1.88 m 2 respectively, which was 8.55 m 2 larger than that of positive and negative steering gearbox. The crawler with positive and negative steering gearbox has minor damage to paddy soil. This research can provide a theoretical basis for the smooth steering in situ and structural optimization of the crawler steering gearbox.

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“…To solve the above problems, this paper combines the model predictive control and agricultural transport vehicle to design navigation controller to realize the trajectory tracking of agricultural vehicles. Model predictive control is widely used in automatic vehicle navigation [26,27] , active front wheel steering [28,29] and other aspects. It can make up for the uncertainty caused by model mismatch, time change and interference.…”

Section: Introduction mentioning

confidence: 99%

Trajectory tracking control of agricultural vehicles based on disturbance test

Liu

Zheng

Wang

et al. 2020

International Journal of Agricultural and Biological Engineering

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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.

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Design of obstacle avoidance controller for agricultural tractor based on ROS

Cited by 13 publications

References 13 publications

Path Tracking Control of an Autonomous Tractor Using Improved Stanley Controller Optimized with Multiple-Population Genetic Algorithm

Path Tracking Control of an Autonomous Tractor Using Improved Stanley Controller Optimized with Multiple-Population Genetic Algorithm

Developments of crawler steering gearbox for combine harvester straight forward and steering in situ

Trajectory tracking control of agricultural vehicles based on disturbance test

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