Navigation method and self-walking device
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Solution Overview
Problem
Self-walking devices, such as sweeping robots, face inefficiencies in navigation due to inadequate obstacle avoidance, leading to missed cleaning areas behind obstacles like doorsills and carpet edges, resulting in reduced sweeping coverage.
Innovation Solution
A navigation method for self-walking devices that determines candidate regions based on environmental and historical data, identifying passable obstacles and reachable positions to enable the device to enter and clean previously skipped areas, using structured light point cloud, laser ranging, and image information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the self-walking device avoids all obstacles during navigation, then collision prevention is improved, but cleaning coverage deteriorates due to missed areas behind passable obstacles
Solution Approach 1:
The patent applies local quality by differentiating obstacle types and applying different navigation strategies to different regions. Passable obstacles (doorsills, carpet edges) are identified and marked as candidate regions for cleaning, while impassable obstacles are avoided. This localized differentiation allows the device to clean behind passable obstacles while still avoiding collisions with true obstacles.
Solution Approach 2:
The patent changes the parameter of obstacle classification from binary (avoidable/unavoidable) to multi-category (passable/impassable). By using structured light point cloud information, laser ranging, and image information to determine obstacle characteristics, the system transforms obstacle parameters to identify candidate regions that should be cleaned rather than avoided.
2Measurement precision
If the self-walking device uses multiple sensing methods to identify passable obstacles, then navigation precision is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple sensing methods (structured light point cloud information, laser ranging information, and image information) into a unified obstacle recognition system. By combining these different data sources, the system achieves high-precision identification of passable obstacles while sharing processing resources across the different sensor types.
Solution Approach 2:
The patent creates a universal navigation system that handles both traditional obstacle avoidance and candidate region identification using the same hardware platform. The processing unit universally processes data from all sensor types to perform both collision prevention and cleaning coverage optimization functions.
3Productivity
If the self-walking device enters candidate regions to clean missed areas, then cleaning coverage is improved, but navigation time increases due to additional positioning and movement
Solution Approach 1:
The patent performs preliminary identification of candidate regions during the main cleaning task using real-time sensor data. By pre-identifying passable obstacles and marking candidate regions before completing the current cleaning cycle, the system prepares navigation targets in advance, reducing the need for extensive re-positioning and minimizing additional navigation time.
Solution Approach 2:
The patent uses feedback from structured light, laser ranging, and image sensors to continuously update the map and identify candidate regions. This real-time feedback allows the system to dynamically adjust its navigation path and efficiently integrate candidate region cleaning into the existing navigation routine rather than treating them as separate tasks.
Data Source
AI summary
Disclosed are a navigation method and a self-walking device. The navigation method is applied to the self-walking device and includes: determining a candidate region after a current task is completed; determining whether a reachable position adjacent to the candidate region exists; and controlling, in response to an existence of the reachable position adjacent to the candidate region, the self-walking device to reach the reachable position, and controlling the self-walking device to attempt to enter the candidate region to operate in the candidate region.