Path Planning Based on ADFA* Algorithm for Quadruped Robot

Path Planning Based on ADFA* Algorithm for Quadruped Robot

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At present, la rams crop top the path-planning algorithm based on the grid map is generally adopted in the field of quadruped robot and the obtained environmental information is represented by a standardized grid map.In this paper, the ADFA* algorithm introduces a dilation factor based on the DFA* to solve the path planning problem under the constraint of computing time and provide a path search result related to the time limit.Path-planning algorithms based on raster maps often equate robots with particles, causing problems, such as path blocking.The FA* algorithm adds raster tolerance to expand obstacles.DFA* uses a path-splitting approach that, such as the DA* algorithm, has better dynamic environment processing capabilities than the FA*.

However, during the here actual operation of the robot, the environmental information acquired is extremely frequent due to its instability.The robot itself is often in a relatively static state.Therefore, compared with obtaining the shortest path, it is more practical to improve the path search efficiency under dynamic map environment.ADFA* will gradually optimize the path and eventually get the optimal solution when time is sufficient.When the time is limited, ADFA* will search for the current optimal solution under the specified search time but may not be able to obtain the shortest path, which is called the second best solution.