Cloud Robot Navigation Using Real-Time Point Cloud Positioning
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Solution Overview
Problem
Current positioning methods for robots, such as laser radar and GPS, face challenges in processing the large amount of data from three-dimensional building models and point cloud maps in real time, leading to inefficient navigation.
Innovation Solution
A method that involves receiving real-time point cloud information from a robot, determining its current position, planning multiple motion paths using a heuristic search algorithm, and sending the optimal path to the robot for navigation, with calculations performed on a cloud server to improve navigation speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser radar positioning method and point cloud map construction are used, then positioning accuracy is improved, but data processing time increases and real-time navigation becomes difficult
Solution Approach 1:
The patent introduces a cloud server as an intermediary between the robot and the positioning system. The robot sends point cloud data to the cloud server, which performs the computationally intensive tasks of point cloud map construction and positioning calculation. This mediator approach allows the robot to maintain simple onboard hardware while achieving high positioning accuracy through external cloud computing resources.
Solution Approach 2:
The patent replaces the traditional mechanical/local processing system with a cloud-based computing system. Instead of requiring the robot to locally process large amounts of point cloud data in real-time, the system substitutes this with remote cloud computing capabilities, effectively replacing the need for complex onboard processing hardware with networked computational resources.
2Measurement precision
If complex path planning algorithms are implemented locally, then navigation accuracy is improved, but computational load increases and navigation speed decreases
Solution Approach 1:
The cloud server acts as an intermediary that handles complex path planning calculations. The robot sends its current position and target position to the cloud server, which then performs multi-path planning and optimization using advanced algorithms. This allows the robot to maintain simple onboard processing while achieving high navigation accuracy through cloud-based computational power.
Solution Approach 2:
The system performs preliminary path planning calculations on the cloud server before the robot executes the navigation. By pre-calculating multiple possible paths and selecting the optimal one in advance, the system reduces the computational burden during actual navigation, thereby improving navigation speed without sacrificing accuracy.
Data Source
AI summary
A positioning and navigation method for a robot includes: receiving point cloud information of a current position and information of a target position sent by a robot, wherein the point cloud information of the current position is updated in real time; determining the current position of the robot according to the point cloud information; planning a plurality of motion paths according to the current position and the target position; searching for an optimal path among the plurality of motion paths by a predetermined heuristic search algorithm; and sending the current position of the robot and the optimal path to the robot, such that the robot moves according to the optimal path.