The invention is suitable for the technical field of computers, and particularly relates to a navigation method, a device, a navigation robot and a storage medium. The navigation method includes the following steps that initial position information and target position information are obtained; path planning is conducted according to the initial position information, the target position informationand a pre-established navigation area digital map; a robot moves toward a target position according to the planned path and current position information is obtained; the path is re-planned accordingto the current position information, the target position information and the navigation area digital map; and the robot moves toward the target position according to the re-planned path, and the previous steps are repeated until the robot reaches the target position. Path planning is conducted before moving, after the current position information is obtained in the advancing process, path planningis carried out again until the target position is reached, the advancing path can be adjusted constantly in this way, new obstacles in the path are avoided, and movement time consuming is reduced.

Navigation method, device, navigation robot and storage medium

The invention discloses a robot trajectory tracking method, a robot trajectory tracking system and a storage medium which integrate the trajectory optimization and control, and better ensure the feasibility of trajectory tracking of a robot. When the robot passes through a dense obstacle, the weight in the target function is correspondingly adjusted according to the shortest distance between the current position of the differential robot and the obstacle by adopting the self-adaptive weight, so that the safety and the running speed can be considered when the robot performs trajectory tracking,and the trajectory tracking performance of an obstacle area is improved. According to the method, the obstacle avoidance constraint is put into the target function and is converted into the soft constraint, the optimal control input is found in the mode of sampling in the allowable control space, the non-convex optimization problem is solved, and meanwhile, the obstacle avoidance performance of the mobile robot is improved in the mode of dynamically adjusting the weight.

Robot trajectory tracking method and system and storage medium

The invention aims to provide a driverless automobile local path planning performance evaluation method. According to the method, the performance of driverless vehicle local path planning algorithms based on graph searching in the prior art can be quantitatively evaluated, advantages and disadvantages of the algorithms are measured, the optimal algorithm is selected to be applied to the field of driverless automobiles, or debugging and optimizing parameters of the path planning algorithm are facilitated, so the performance of the path planning algorithm is improved, and the autonomous navigation capability of the driverless automobiles is promoted.

Driverless automobile local path planning performance evaluation method

The invention discloses an improved DWA dynamic window method for path following and obstacle avoidance of an unmanned ship. The method comprises the following steps: S1, acquiring a maximum angular speed and minimum angular speed corresponding to a left full rudder and a right full rudder, enabling the right full rudder to be the minimum angular speed, and enabling the left full rudder to be themaximum angular speed; S2, uniformly sampling any number of angular speeds in the closed interval of the minimum angular speed and the maximum angular speed in the S1 and enabling one angular speed tocorrespond to one rudder angle; S3, selecting simulation time t to be any numerical value, enabling a simulation time interval -t to be any numerical value, and enabling an unmanned ship speed V to be numerical value; and S4, substituting the simulate time, the simulation time interval and the unmanned ship speed in the S3 into an unmanned ship motion formula. According to the invention, a methodwhich is good in path following and obstacle avoidance performance, good in real-time performance and high in calculation efficiency can be found conveniently; and when the unmanned ship sails alongthe path, obstacles can be avoided in real time. The method is convenient to use.

Improved DWA dynamic window method for path following and obstacle avoidance of unmanned ship

The invention relates to a global dynamic path planning algorithm for multiple virtual target points based on a dynamic window. A dynamic window method is applied to the global path planning direction, and the defect that traditional global path planning is discontinuous and unsmooth is improved; and as for specific operation, by adding the multiple virtual target points, updating the course angleof an unmanned vehicle on the special position and adding random obstacles, global dynamic path planning of the unmanned vehicle is achieved, and the global dynamic path planning algorithm is appliedto complex environments such as 8-surrounding tracks in 'Formula Student Autonomous China'. The MATLAB simulation result shows that the unmanned vehicle can effectively avoid the obstacles occurringrandomly, and global path planning and tracing are safely and stably completed.

Global dynamic path planning algorithm for multiple virtual target points based on dynamic window

The invention relates to an automatic driving unmanned vehicle bidirectional dynamic path planning method based on an A star algorithm. The automatic driving unmanned vehicle bidirectional dynamic path planning method comprises the following steps of: carrying out initialization, loading a grid map, and setting positions of a starting point and a target point and a movement step length of an unmanned vehicle; creating two open lists and two close lists, which are respectively used for searching along a direction from the starting point to the target point by using the A-star algorithm and searching along a direction from the target point to the starting point by using the A-star algorithm; when the same node appears in two open lists, representing that an optimal path in a current map environment is found, then setting a new position as a new starting point by moving the position of the unmanned vehicle, and ending movement of the unmanned vehicle by judging whether the new position isthe position of the target point; and when the unmanned vehicle does not reach a target position, updating map information, and repeating the path finding and moving process until the unmanned vehicle reaches the target position. According to the invention, a path finding speed is improved by respectively using the A-star algorithm for the starting point and the target point, and the automatic driving unmanned vehicle bidirectional dynamic path planning method also can be adapted to a changing environment.

Automatic driving unmanned vehicle bidirectional dynamic path planning method based on A-star algorithm

The invention relates to a path planning method based on a concentric circle sampling guide RRT algorithm. The method comprises the following steps of: 1, taking the starting point of path planning asthe root node of a random tree; 2, generating a random point by concentric circle sampling; 3, judging whether the random point is in a map range or not, if so, turning to the step 4, otherwise, returning to the step 2 to regenerate a random point; 4, finding out a node closest to the random point as an adjacent point; 5, generating a new node by extending step length from the adjacent point to the random point; 6, judging whether an obstacle exists between the new node and the adjacent point or not, if so, returning to the step 2 to perform resampling, and otherwise, adding the new node intothe random tree; 7, judging whether the new node is in a target point area or not, if so, adding a target point into the random tree, backtracking from the target point to the root node to obtain thepath points of a planned path, and otherwise, returning to the step 2; and 8, fitting the path points to obtain a final path. The method is beneficial to improving path finding efficiency and quicklyfinding the planned path.

Path planning method based on concentric circle sampling guide RRT algorithm

The invention relates to an automobile high-speed working condition anti-collision rear-end collision device and method, and the method comprises the following steps: 1), the state information of a vehicle running in front of the same lane, the information of a vehicle running behind the same lane and the information of a vehicle running on an adjacent lane during the high-speed running of an automobile are detected; 2) when the vehicle running in front of the same lane is braked suddenly, the vehicle decelerates and keeps a safe distance from the front vehicle, and when the vehicle decelerates to a lower limit value, the vehicle runs according to the following method: when no vehicle runs behind the same lane, the automatic driving module controls the vehicle to decelerate continuously and keep a safe distance from the front vehicle on the same lane; when there is a driving vehicle behind the same lane and there is no driving vehicle in front of and behind the adjacent lane, the pathplanning module plans a lane changing track, and the automatic driving module controls the vehicle to drive according to the lane changing track and change the lane to the adjacent lane. The device and the method are beneficial to avoiding collision and rear-end collision between the automobile and surrounding driving vehicles during high-speed driving, and the driving safety is improved.

Xiao Jiliang

Papers

Global dynamic path planning algorithm for multiple virtual target points based on dynamic window

Automatic driving unmanned vehicle bidirectional dynamic path planning method based on A-star algorithm

Path planning method based on concentric circle sampling guide RRT algorithm

Automobile high-speed working condition anti-collision rear-end collision device and method