Robot dog inspection path intelligent planning and dynamic adjusting method, system and device and medium

By employing a path planning method based on multi-objective adaptive optimization and real-time obstacle updates, the inefficiency of path planning and energy management in the robot dog inspection system is solved, enabling rapid response to emergency tasks and power management, thereby improving the execution efficiency and reliability of inspection tasks.

CN121632149APending Publication Date: 2026-03-10GUIZHOU POWER GRID CO LTD
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Patent Information

Application Number
CN202511834773.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-08
Publication Date
2026-03-10

AI Technical Summary

Technical Problem

Existing robot dog inspection systems suffer from inefficiency and unreliability in path planning and energy management. They fail to comprehensively consider the urgency of the task, the difficulty of the terrain, and energy consumption, resulting in unreasonable path planning and frequent replanning or power depletion.

Method used

A multi-objective adaptive optimization path planning method is adopted, which combines task urgency, terrain difficulty and energy prediction. The global path is generated by the A* algorithm and the obstacle layer is updated in real time. Local path correction or global replanning is performed, and the charging strategy is dynamically adjusted in combination with the energy management module.

Benefits of technology

It improves the efficiency and reliability of robot dog inspection tasks, ensures timely inspection of critical equipment and avoids power depletion, and adapts to path planning in complex environments.

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Abstract

The invention discloses a robot dog inspection path intelligent planning and dynamic adjustment method, system and device and a medium, and belongs to the technical field of robot path planning, and the method comprises the steps: calculating a task emergency degree index according to a weight coefficient of an inspection point and a time constraint, and determining a task priority; constructing a hierarchical electronic map containing the terrain difficulty coefficient and the moving cost; performing global path planning through a comprehensive cost function by adopting an A star algorithm; environment information is collected in real time through multiple sensors, and the dynamic obstacle layer is updated; performing real-time trajectory optimization by adopting a local path planning mode; selecting local path correction or global path re-planning according to the path execution state score; energy needed for completing the remaining tasks is predicted, and a charging path is planned when necessary. According to the invention, multi-target adaptive optimization of path planning is realized, a coordination mechanism of global planning and local adjustment is established, and the execution efficiency and reliability of inspection tasks are improved.
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