Motion characteristics of the robotic arm can dominate the performance of mango harvesting vehicles during picking. In this study, the kinematics analysis was carried out using the multi-body dynamics theory. An initiative was first undertaken to conceptualize and engineer a mango harvesting vehicle. The higher efficiency and labor-saving harvesting was achieved within tropical agricultural regions, compared with the manual. The equipment was designed with walking, lifting, and harvesting functions that were tailored to the Hainan mango planting environment, growth and harvesting agronomy. The core components of the vehicle included a hexapod bionic walking device, a robotic arm, and an end-effector. However, the harvested mangoes were of a modest size within the available operational range, resulting in a low load on the harvesting vehicle. The kinematics model of the robotic arm was established using the Denavit-Hartenberg (D-H), according to the growth of mangoes, the geometric and vector configuration of the robotic arm. The variable separation was employed to conduct the inverse kinematics on the joint variables of the robotic arm. The end-effector motion space planning was also conducted to systematically clarify the motion. The trajectory planning showed that the stability of end-effector motion fully met the motion requirements of the robotic arm during picking. The dynamic model of the robotic arm was constructed by the Lagrangian method. The forward and inverse dynamics simulation was carried out on the joint motion of the robotic arm under constant torque and only periodic swing using Adams software. The dynamic analysis showed that there was a certain periodicity movement under the constant torque in the telescopic and swing devices. The peak of the stage reached about 1.25, 2.3, and 4.15 s. In the case of only oscillating periodic motion, the driving torques of the rotating and oscillating device were approximately cyclically changed, with the peak values of 72.5, and 52 N·mm, respectively, indicating two maximum values in one motion cycle. A vibration analysis was also performed to determine the dynamic performance of the robotic arm. The feasibility of the multi-body dynamics model was verified using linear modal calculations and experiments. A vibration element was then created at the bottom of the robotic arm, in order to explore the effect of the bottom vibration excitation on the motion of the end-effector. The frequency response curve showed that the end-effector was subject to the greatest vibration in the y-direction during the operation of the robotic arm, leading to the overall vibration. Moreover, there was a relatively gentle amplitude in the y-direction between 0-10 Hz. Parametric calculations were then performed, where the y direction of the end-effector was defined as the target for optimization. The maximum response value of the robotic arm was 0.1665, indicating the minimal vibration to fully meet the specified smooth operation. In conclusion, the mango harvesting vehicle can be an effective solution to the challenges posed by manual mango picking in tropical agricultural areas. The trajectory planning shared the efficient and precise movement of the end-effector, meeting the requirements of mango harvesting. The multi-body dynamics model of the mango-picking robotic arm was verified by experiments. The findings can provide a strong reference for the picking performance of the robot arm for its high reliability and stability.