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Path planning of intelligent forklift based on polynomial spiral line
Published:2022-12-20 author:SHEN Hong-jiao, QIU Ji-hong, XU Fang. Browse: 1224 Check PDF documents
Path planning of intelligent forklift based on polynomial spiral line

SHEN Hong-jiao1,2,3, QIU Ji-hong1,2,4, XU Fang1,2,4

(1.State Key Laboratory of Robotics, Shenyang Institute of Automation (Chinese Academy of Sciences), Shenyang 
110016, China; 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 
110169, China; 3.University of Chinese Academy of Sciences, Beijing 100049, China;
4.Shenyang SIASUN Robot & Automation Co.Ltd., Shenyang 110168, China)

Abstract:  Aiming at solving the problem of accurate connection between the current-point and the goal-point of forklift, a path planning method based on polynomial spiral line was proposed. Firstly, the operation process of forklift was analyzed, and the task of forklift path planning was clarified. Then, the kinematics model of forklift and the basic properties of polynomial spiral line were studied, the target point was transformed to the unit circle of the first quadrant by using the symmetry and scaling of polynomial spiral line, the number of optimization variables was reduced by using the linear relationship of polynomial coefficients, the start and end state constraints of path as well as the kinematic constraints of forklift were considered, the objective function of minimizing curvature cost based on polynomial spiral line was constructed. Finally, 23 typical planning scenarios were selected to verify the algorithm in MATLAB. The results show that the path meets the state constraints of the starting point and the target point, which satisfies operation requirements of forklift; the path curvature conforms to the kinematic constraints of the forklift; the algorithm has no special need for the steering angle of the planned starting point and is still applicable to the scene with large deviation of the transverse distance and heading angle of the target point, which verifies the feasibility of the algorithm.
Key words:  loading and unloading machinery; state constraints; kinematic constraints; forklift kinematics model; minimizing curvature cost; objective function; path curvature

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