Robot whole-situation path planning method facing uncertain environment of mixed terrain and region

Abstract

The invention discloses a robot whole-situation path planning method facing an uncertain obstacle environment of mixed terrain and region, aiming to enabling the robot to finish a task by the lowest risk degree under a mixed terrain environment. The robot whole-situation path planning method comprises the following steps of: (1) detecting and constructing a robot working environment model comprising a movement starting point, a target point, static obstacle position and shape, a possible covering region of an uncertain obstacle, and covering terrain type and region; (2) adopting a weighting passable length of a terrain passable degree as a path evaluation performance index I; (3) adopting a path containing degree for describing an uncertain obstacle covering region covering degree as a path evaluation performance index II; (4) constructing a path feasible region according to a penetration degree between static obstacles to realize efficient path feasibility judgment and repairing; (5) extracting an advantage path public segment for automatically generating a feasible path; and (6) aiming at two performance indexes of the steps (3) and (4), adopting a multi-target cultural algorithm to realize path evolution and optimization.

Description

technical field [0001] The invention relates to a global path planning method for a robot, in particular to a global path planning method for a robot facing uncertain environments in mixed terrain areas. Background technique [0002] Robot path planning refers to finding the most reasonable and efficient obstacle avoidance path from the starting point to the target point in an environment with obstacles distributed. The path is often the best in a certain performance, such as the shortest distance, the shortest movement time and so on. A good path planning scheme is the prerequisite for ensuring that the robot can complete tasks efficiently. [0003] According to the robot's grasp of the environment, the existing planning methods can be divided into model-based global path planning methods and detection information-based local path planning methods. The local path planning method has good real-time performance, but it cannot guarantee that the robot will eventually reach t...

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Problems solved by technology

[0006] Secondly, the traditional global path planning method has the following limitations when dealing with obstacle avoidance problems: it does not distinguish between obstacles with regional uncertainty and obstacles with fixed positions and shapes, and the traditional method of dealing with obstacles is used to deal with such obstacles. When there are uncertain obstacles in the area, it will cause the path to transition avoidance of such obstacles, which will affect the path optimization effect

However, since the inserted feasible points are randomly selected, the repaired path may still be infeasible, so iterative repairs are often required to meet the feasible conditions

Obviously, this path repair strategy consumes a lot of computing time and reduces the efficiency of path planning

In addition, the existing methods lack an integrated judgment and repair mechanism that can organically integrate the path’s feasibility judgment and infeasible path’s repair strategy, resulting in increased computational complexity

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