The application of mobile robots is an important link in the development of intelligent greenhouses. In view of the complex environment of a greenhouse, achieving precise positioning and navigation by robots has become the primary problem to be solved. Simultaneous localization and mapping (SLAM) technology is a hot spot in solving the positioning and navigation in an unknown indoor environment in recent years. Among them, the SLAM based on a two-dimensional (2D) Lidar can only collect the environmental information at the level of Lidar, while the SLAM based on a 3D Lidar demands a high computation cost; hence, it has higher requirements for the industrial computers. In this study, the robot navigation control system initially filtered the information of a 3D greenhouse environment collected by a 3D Lidar and fused the information into 2D information, and then, based on the robot odometers and inertial measurement unit information, the system has achieved a timely positioning and construction of the greenhouse environment by a robot using a 2D Lidar SLAM algorithm in Cartographer. This method not only ensures the accuracy of a greenhouse environmental map but also reduces the performance requirements on the industrial computer. In terms of path planning, the Dijkstra algorithm was used to plan the global navigation path of the robot while the Dynamic Window Approach (DWA) algorithm was used to plan the local navigation path of the robot. Through the positioning test, the average position deviation of the robot from the target positioning point is less than 8 cm with a standard deviation (SD) of less than 3 cm; the average course deviation is less than 3° with an SD of less than 1° at the moving speed of 0.4 m/s. The robot moves at the speed of 0.2, 0.4, and 0.6 m/s, respectively; the average lateral deviation between the actual movement path and the target movement path is less than 10 cm, and the SD is less than 6 cm; the average course deviation is <3°, and the SD is <1.5°. Both the positioning accuracy and the navigation accuracy of the robot can meet the requirements of mobile navigation and positioning in the greenhouse environment.

Background: The parallel mechanism is widely used in motion simulators, parallel machine tools, medical equipment and other fields. It has advantages of high rigidity, stable structure and high carrying capacity. However, the control strategy and control method are difficult to study because of the complexity of the parallel mechanism system. Objective: The purpose of this paper was to verify the dynamic model of a hydraulic driven 3-DOF parallel mechanism and propose a compound control strategy to broaden the bandwidth of the control system. Methods: The single rigid body dynamic model of the parallel mechanism was established by the Newton Euler method. The feed forward control strategy based on joint space control with inverse kinematic was designed to improve the bandwidth and control precision. The co-simulation method based on MATLAB / SIMULINK and ADAMS was adopted to verify the dynamics and control strategy. Results: The bandwidth of each degree of freedom in the 3-DOF parallel mechanism was used to expand about 10Hz and the amplitude error was controlled below 5%. Conclusion: Based on the designed dynamic model and composite control strategy, the controlled accuracy of the parallel mechanism is improved and the bandwidth of the control system is broadened. Furthermore, the improvements can be made in aspects of control accuracy and real-time performance to compose more patents on parallel mechanisms.