Abstract: A self-learning method for an obstacle and a self-learning method for a new obstacle are provided. With the self-learning method, in step 1, data of a grid map in a movement region is acquired, and each of grids of the grid map is marked as not being traversed. In step 2, a starting grid of the grid map is set, data of the starting grid is pushed into a stack, a movement unit is controlled to move to the starting grid, and the starting grid is remarked as being traversed. In step 3, the movement unit is controlled to traverse the grid map, and boundary data of the obstacle is acquired based on marks of the grids in the grid map. In step 4, boundary data of the obstacle is stored.

Abstract: An integrated navigation method for a mobile vehicle is provided, which includes: acquiring a motion measurement of the mobile vehicle by using an inertial navigation element in the mobile vehicle and calculating a gesture parameter of the mobile vehicle based on the motion parameter; estimating, based on the gesture parameter, a motion state of the mobile vehicle in a real time manner by using a satellite navigation element in the mobile vehicle to obtain an error estimation value of the motion state, and correcting a motion parameter of the mobile vehicle based on the error estimation value of the motion state; and controlling an operation route of the mobile vehicle based on corrected navigation information.

Abstract: The present invention relates to the field of navigation. Disclosed is a route planning method for a mobile vehicle, comprising: partitioning an operation area of a mobile vehicle into blocks using a grid cell as a minimum unit to obtain operation blocks, and performing a reciprocating operation in each operation block in a traversing manner; after the mobile vehicle completes the operation in one operation block, moving to another operation block to perform the reciprocating operation therein in the same traversing manner. The present invention can cause a mobile vehicle to obtain a plurality of operation blocks on the basis of an electronic grid map of known information by means of a block partitioning algorithm, and plan an operation route in each operation block by means of a reciprocating and traversing route planning algorithm in each operation block.

Abstract: A path tracking method is provided. The path tracking method includes obtaining a current location and a current traveling direction of the mobile vehicle, and determining a traveling path along which the mobile vehicle travels to a destination based on the current location and the current traveling direction; simplifying the mobile vehicle into a differential model, establishing a forward objective function of the differential model in the traveling path, and obtaining an optimal solution of the forward objective function; and controlling a speed of the mobile vehicle corresponding to the differential model by using the optimal solution as an optimal differential control variable, until the mobile vehicle reaches the destination. The path tracking method is simple in calculation, adopts algorithms that is naturally stable, and is used in combination with integrated navigation, thereby ensuring stability and reliability of tracking.

Abstract: The GNSS-RTK-based positioning method includes the following steps: Step 1, performing data quality control according to analyzed raw satellite-ground observation values; Step 2, performing SPP positioning by using a pseudorange observation value, and performing RTD positioning according to an RTD pseudorange residual of a previous epoch and a pseudorange residual of a current epoch obtained through SPP positioning calculation; Step 3, calculating a float solution by means of the least squares method and Kalman filtering of additional ambiguity parameters in which the RTD positioning result is used as an initial value; and Step 4, converting the float ambiguity solution into a fixed solution by using an optimized partial ambiguity fixing strategy.

Abstract: The GNSS-RTK-based positioning method includes the following steps: Step 1, performing data quality control according to analyzed raw satellite-ground observation values; Step 2, performing SPP positioning by using a pseudorange observation value, and performing RTD positioning according to an RTD pseudorange residual of a previous epoch and a pseudorange residual of a current epoch obtained through SPP positioning calculation; Step 3, calculating a float solution by means of the least squares method and Kalman filtering of additional ambiguity parameters in which the RTD positioning result is used as an initial value; and Step 4, converting the float ambiguity solution into a fixed solution by using an optimized partial ambiguity fixing strategy.

Abstract: An integrated navigation method for a mobile vehicle is provided, which includes: acquiring a motion measurement of the mobile vehicle by using an inertial navigation element in the mobile vehicle and calculating a gesture parameter of the mobile vehicle based on the motion parameter; estimating, based on the gesture parameter, a motion state of the mobile vehicle in a real time manner by using a satellite navigation element in the mobile vehicle to obtain an error estimation value of the motion state, and correcting a motion parameter of the mobile vehicle based on the error estimation value of the motion state; and controlling an operation route of the mobile vehicle based on corrected navigation information.

Abstract: A self-learning method for an obstacle and a self-learning method for a new obstacle are provided. With the self-learning method, in step 1, data of a grid map in a movement region is acquired, and each of grids of the grid map is marked as not being traversed. In step 2, a starting grid of the grid map is set, data of the starting grid is pushed into a stack, a movement unit is controlled to move to the starting grid, and the starting grid is remarked as being traversed. In step 3, the movement unit is controlled to traverse the grid map, and boundary data of the obstacle is acquired based on marks of the grids in the grid map. In step 4, boundary data of the obstacle is stored.

Abstract: The present invention relates to the field of navigation. Disclosed is a route planning method for a mobile vehicle, comprising: partitioning an operation area of a mobile vehicle into blocks using a grid cell as a minimum unit to obtain operation blocks, and performing a reciprocating operation in each operation block in a traversing manner; after the mobile vehicle completes the operation in one operation block, moving to another operation block to perform the reciprocating operation therein in the same traversing manner. The present invention can cause a mobile vehicle to obtain a plurality of operation blocks on the basis of an electronic grid map of known information by means of a block partitioning algorithm, and plan an operation route in each operation block by means of a reciprocating and traversing route planning algorithm in each operation block.

Abstract: A path tracking method is provided. The path tracking method includes obtaining a current location and a current traveling direction of the mobile vehicle, and determining a traveling path along which the mobile vehicle travels to a destination based on the current location and the current traveling direction; simplifying the mobile vehicle into a differential model, establishing a forward objective function of the differential model in the traveling path, and obtaining an optimal solution of the forward objective function; and controlling a speed of the mobile vehicle corresponding to the differential model by using the optimal solution as an optimal differential control variable, until the mobile vehicle reaches the destination. The path tracking method is simple in calculation, adopts algorithms that is naturally stable, and is used in combination with integrated navigation, thereby ensuring stability and reliability of tracking.