Travel control method, device, and storage medium
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Solution Overview
Problem
Existing floor sweeping robots face challenges in accurately judging obstacles due to limitations in their ability to detect three-dimensional environments, leading to inaccurate obstacle avoidance and potential collisions with narrow gaps or uneven surfaces.
Innovation Solution
The method involves collecting three-dimensional environment information using an area array solid-state laser radar, identifying types of obstacles (to be climbed over, stepped down, or traversed), and performing targeted travel controls based on this information to improve obstacle avoidance performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional distance sensors (infrared, laser, ultrasonic) are used for obstacle detection, then the device complexity is low, but the measurement precision and three-dimensional environment detection capability are insufficient
Solution Approach 1:
The patent replaces traditional mechanical distance sensors (infrared, laser, ultrasonic) with a vision-based system comprising a camera and point cloud processing. This substitution enables three-dimensional environment perception and precise obstacle detection while avoiding the limitations of conventional distance sensors in accurately judging obstacle types and dimensions
Solution Approach 2:
The patent transitions from two-dimensional distance measurement to three-dimensional spatial perception by using a camera to capture images and generate point cloud data. This dimensional enhancement allows the system to accurately detect obstacle height, width, depth, and spatial position, enabling precise judgment of whether obstacles are gaps, steps, or other terrain features
2Reliability
If simple distance sensors are used, then the device complexity is low, but the reliability of obstacle avoidance is insufficient due to inaccurate obstacle type judgment
Solution Approach 1:
The patent replaces unreliable distance sensor-based obstacle classification with a vision-based system that captures three-dimensional spatial information. This substitution enables accurate differentiation between obstacles that require avoidance (gaps) and those that can be traversed (steps, small obstacles), significantly improving obstacle avoidance reliability
Solution Approach 2:
The patent introduces point cloud processing as an intermediary between image capture and obstacle classification. The point cloud data serves as a mediator that translates visual information into precise three-dimensional spatial measurements, enabling reliable judgment of obstacle characteristics and appropriate navigation decisions
3Adaptability or versatility
If traditional sensors are used for obstacle detection, then the ease of operation is maintained, but the adaptability to different terrain types (narrow gaps, uneven surfaces) is insufficient
Solution Approach 1:
The patent enhances terrain adaptability by transitioning from one-dimensional distance measurement to three-dimensional spatial perception. This dimensional upgrade enables the system to accurately detect and classify various terrain types including narrow gaps, steps, slopes, and uneven surfaces, allowing the navigation system to adapt its behavior to different environmental conditions
Solution Approach 2:
The patent creates a universal detection system that can handle multiple terrain types and obstacle categories using a single integrated vision-based approach. The system can identify and respond to gaps, steps, small obstacles, and uneven surfaces, providing versatile adaptability across diverse cleaning environments without requiring multiple specialized sensors
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and effectiveness of obstacle avoidance, allowing the robot to safely navigate various terrain types, including narrow gaps and uneven surfaces, by adapting its travel path accordingly.
Implementation Method 1
The area array solid-state laser radar is configured to collect three-dimensional environment information on a travel path of the self-mobile device
Data Source
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AI summary
The embodiments of the present disclosure provide a method of travel control, a device and a storage medium. In some exemplary embodiments of the present disclosure, a self-mobile device collects three-dimensional environment information on a travel path of itself in the travel process, identifies an obstacle area and a type thereof existing on the travel path of the self-mobile device based on the three-dimensional environment information, and the self-mobile device adopts different travel controls in a targeted manner for different types of the area, such that the obstacle avoidance performance of the self-mobile device is improved by adopting the method of the travel control in the present disclosure.