Abstract
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. Keywords: ROS, obstacle avoidance, nonlinear model prediction, agricultural tractor DOI: 10.25165/j.ijabe.20191206.4907 Citation: Liu Z D, Lv Z Q, Zheng W X, Zhang W Z, Cheng X X. Design of obstacle avoidance controller for agricultural tractor based on ROS. Int J Agric & Biol Eng, 2019; 12(6): 58–65.
Highlights
Path tracking of agricultural vehicles is the key technology for the automation and intelligence of agricultural machinery[1]
The obstacle avoidance ability of vehicles is an important indicator of the intelligence of vehicles
In the design process of the obstacle avoidance controller, improving the control accuracy and the vehicle dynamic performance of the agricultural tractors still pose a challenge during the trajectory following maneuvering[11,15,16]
Summary
Path tracking of agricultural vehicles is the key technology for the automation and intelligence of agricultural machinery[1]. The obstacle avoidance system of agricultural vehicles involves two key technologies of precise positioning and path re-planning of vehicles[2,3,4]. The local path tracking algorithm is the main method to realize the obstacle avoidance of agricultural vehicles. From the current stage of agricultural navigation, Multi-sensor and multi-algorithm fusion technology have gained a lot of attention to improve efficiency during the obstacles detecting process. In the design process of the obstacle avoidance controller, improving the control accuracy and the vehicle dynamic performance of the agricultural tractors still pose a challenge during the trajectory following maneuvering[11,15,16]. Vol 12 No. proposes a pre-SLAM mapping of the tracking area, which further improves the positioning accuracy and real-time performance of agricultural vehicles[21,22]. Using the model predictive control algorithm, multiple constraints can be taken into considerations in the process of path planning to compensate for the modeling uncertainties, especially at high speed and complex road conditions
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