Workspace simulation and trajectory planning for tomato sorting Delta robot.

Robotic simulations are an effective approach to validate various models and design schemes. A tomato sorting Delta parallel mechanism was validated in this study for the purposes of end-effector motion planning via simulation analysis. Real-world conditions of the robot as well as its forward and inverse kinematics were obtained, followed by simulation analysis to determine whether its workspace meets relevant operation requirements. The motion trajectory of the end-effector is planned according to the simulation results and the motion requirements for tomato sorting. A sine modified trapezoidal acceleration curve is applied as the motion law on the arc trajectory of the end-effector; said motion trajectory is found to be smooth and conducive to stable running of the robot based on MATLAB software analysis. A prototype was designed based on the simulation results and utilized to successfully complete 31 sorting tasks in one minute while smoothly and stably running. 摘要 机器人仿真是验证模型正确性和设计方案可行性的重要方法,为了验证番茄分拣 Delta 机器人尺寸的设 计合理性,以及对机器人末端执行器进行运动规划,本文仿真分析了番茄分拣 Delta 机器人的作业空间,规划 了末端执行器的运动轨迹。 首先,分析番茄分拣 Delta 机器人实际的情况,求取 Delta 机器人末端执行器的运 动学正解和逆解,仿真分析 Delta 机器人的作业空间,验证了其作业空间是否满足作业要求。 然后,根据番茄 分拣的运动要求,规划末端执行器的运行轨迹。 在末端执行器的圆弧运动轨迹上,采用正弦修正梯形加速度曲 线作为运动规律。 采用 MATLAB 软件,仿真验证了番茄分拣 Delta 机器人末端执行器的运动轨迹平滑,运行平 稳。 基于仿真结果设计试验样机,并进行番茄分拣试验,结果表明该番茄分拣 Delta 机器人能够完成 31 次 /min 的番茄分拣任务,且运行平稳。 证明了将 Delta 机器人用于番茄分拣的可行性,以及作业空间和轨迹规 划的合理性。 INTRODUCTION Grading of agricultural products creates added value. In China, the annual yield of tomato products exceeds 34 million tons (Qiao et al., 2014), creating an urgent need for automatic tomato sorting machines (Saber, 2018; Rupanagudi et al., 2014; Huang et al., 2018; Semary et al., 2015). An automatic tomato sorting robot must have rapid speed, high precision, and stable operation for the lossless and accurate sorting of tomatoes. The Delta robot is compact in structure, fast, precise, and is widely used for sorting applications in today’s food and electron industries (Feng et al., 2014; Kuo, 2016; Cheng and Li, 2018; Coronado et al., 2016). Simulations are commonly used to assess research results and establish models (Garg et al., 2018; Mukherjee, 2017); many scholars have investigated the Delta robot via simulation (Zhou and Zhang, 2017; Kidokoro et al., 2015; Hou et al., 2017 ). Jinzhao Du et al., for example, established a simplified dynamic model of the Delta robot and verified its effectiveness by simulation (Du and Lou, 2017). Chi-Sheng Tsai et al. designed a fully operable rotating Delta robot and validated its kinematic model through simulation (Tsai et al., 2016). Jingjun Zhang et al. obtained a constraint equation and Jacobian matrix by analyzing the kinematic mechanism of a Delta robot based on ADAMS software simulations 1 Li Liu, Lect. M. E. Eng.; Jianxing Li, B.E. Stud. Eng.; Zhengkun Li, B.E. Stud. Eng., Qunming Liu, B.E. Stud. Eng.; Yinggang Shi, Assoc. Prof. M.E. Eng.; Yongjie Cui, Prof. Ph.D.Eng. Vol. 58, No. 2 / 2019 178 (Zhang et al., 2009). Tuong Phuoc Tho et al. used the adaptive neuro-fuzzy inference system to solve inverse kinematic problems of a Delta parallel robot; they verified the effectiveness of this method based on virtual reality technology and MATLAB software (Tho et al., 2015). In the present study, MATLAB software was adopted to validate the workspace of a tomato sorting Delta robot and the effectiveness simulation-based trajectory planning. The system construction, kinematic analysis, and simulated end-effector workspace and trajectory are discussed below. An experiment conducted on a prototype robot built according to the simulation results is also discussed below. MATERIALS AND METHODS  System construction The Delta robot-based tomato automatic sorting system is shown in Fig. 1. In this system, the visual sensor takes images of tomatoes on a conveyor belt, processes the images and sends detection results to the controller which drives the robot to classify the fruits into “excellent”, “good”, and “middle” categories. The workspace of the tomato sorting Delta robot includes a section of conveyor belt and tomato collection zone, as shown in Fig. 2. The width of the belt face is 200 mm, and the dimension of the collection zone is 400 mm×150 mm. The bottom diameter of the cylindrical workspace must be larger than 420 mm and the height more than 60 mm to meet the relevant workspace requirements. The Delta robot has a “disc” which gathers and sorts tomatoes. Tomatoes of course are soft and relatively easily damaged – too fast suction or placing speed would harm the product. The sorting speed of the Delta robot can be safely set to 30 m/min.