Autonomous mobile robot and path navigation and path planning method and system thereof

Abstract

The invention discloses an autonomous mobile robot and a path navigation and path planning method and system thereof. The method comprises a global planning process and a local planning process. The method specifically comprises the following steps: acquiring positioning information and sensing information; generating a cost map according to the positioning information and the sensing information,wherein the cost map is used for A-satellite path searching to obtain an initial navigation path; optimizing the initial navigation path, sampling vertexes of the optimized path, and taking out key points from the vertexes for interpolation to obtain a global navigation path; generating a to-be-selected path group according to positioning information and the global navigation path; evaluating each to-be-selected path according to the real-time perception information to obtain an optimal path, and outputting the optimal path; according to the method, the near-optimal navigation path can be quickly searched in a large range, a series of points describing the global navigation path are obtained, the points of the global navigation path are adjusted and selected, and the global navigation path capable of meeting the requirements of continuous curvature and no collision is obtained.

Description

technical field [0001] The invention belongs to the technical field of autonomous mobile robots, and in particular relates to an autonomous mobile robot and its path navigation and path planning methods and systems. Background technique [0002] In unmanned driving systems, path planning is considered in two stages, global planning and local planning. The global planning generates a navigation path from the starting point to the goal point, while the local planning generates a collision-free driving path that satisfies the robot dynamics constraints under the guidance of the global planning path. In this way, the results of the global plan will have a huge impact on the results of the local plan. [0003] The A-star algorithm is one of the most common and effective methods in global programming. However, there is still a gap between most of the results it gives and the optimal solution. In order to solve this problem, some researchers have proposed a method of global path...

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Problems solved by technology

[0004] However, compared with the traditional A-star algorithm, the hybrid A-star algorithm requires a large time overhead and is not complete

However, the front-end result obtained by the A-star algorithm is farther away from the optimal solution in the solution space than the front-end result obtained by the hybrid A-star algorithm. It is difficult to achieve the ideal result by directly using conjugate gradient descent to optimize the results of the A-star algorithm.

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