一种决定移动智能体在执行任务之前所处位置的方法及系统
The MoMa-Pos framework, through graph embedding architecture and the Open TSP algorithm, solves the problem of determining the basic position of a mobile manipulator in complex environments, improves computational efficiency and adaptability, and achieves high efficiency and cost optimization in robot operation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHONGQING UNIV
- Filing Date
- 2024-05-30
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies for determining the basic position of mobile robotic arms in complex environments suffer from problems such as unintelligent manual positioning, high manpower and material costs, difficulty in adapting to different robot models, and failure to effectively consider the impact of obstacles.
The MoMa-Pos framework is adopted, which uses graph embedding architecture to evaluate object importance, calculates potential base positions by combining robot model and environmental features, and optimizes the path to determine the optimal base position through Open TSP algorithm.
It improves the robot's operational performance and adaptability in complex environments, optimizes computational efficiency and response speed, and achieves a balance between cost and performance.
Smart Images
Figure CN118478355B_ABST