Cleaning Device Path Planning for Dynamic Obstacle Adaptation
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Solution Overview
Problem
Current cleaning devices struggle with inadequate whole-house cleaning coverage, particularly in dynamic scenes with obstacles such as people, pets, and moving furniture, leading to unsatisfactory cleaning effects.
Innovation Solution
A cleaning method and apparatus that determines a target cleaning region using semantic maps and obstacle detection, generates a cleaning trajectory, and performs cleaning actions along this trajectory, including edge cleaning and zigzag patterns, while adapting to dynamic obstacles and dust levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cleaning devices use traditional path planning methods, then they can cover large areas, but they fail to identify dynamic obstacles and miss cleaning opportunities in dynamic scenes
Solution Approach 1:
The system performs preliminary identification of dynamic obstacles (people, pets, furniture) before finalizing the cleaning path. The processor identifies objects in the cleaning region and determines their mobility characteristics in advance, then plans the cleaning trajectory accordingly, ensuring both comprehensive coverage and avoidance of dynamic obstacles
Solution Approach 2:
The cleaning path is made dynamic and adjustable based on real-time obstacle identification. The system continuously monitors the cleaning region for moving objects and recalculates the cleaning trajectory when dynamic obstacles are detected, transforming the static path planning into a dynamic adaptive process that maintains high reliability while responding to changing conditions
2Productivity
If cleaning devices clean entire rooms, then they achieve high coverage, but they waste time and energy on already clean areas
Solution Approach 1:
The system applies different cleaning strategies to different regions within the cleaning space. Based on obstacle identification and dust level detection, the processor determines specific cleaning trajectories for localized areas rather than uniformly cleaning entire rooms, concentrating cleaning efforts on regions that actually require attention and avoiding redundant cleaning in already clean areas
Solution Approach 2:
The system uses feedback from dust level detection and obstacle identification to dynamically adjust the cleaning plan. The processor receives information about dust distribution and obstacle locations, then optimizes the cleaning trajectory to focus on high-dust areas while skipping clean regions, improving productivity while reducing time waste through continuous feedback-driven adjustments
Data Source
AI summary
A cleaning method includes: determining a target cleaning region, generating a cleaning trajectory in the target cleaning region in response to a path planning instruction, and performing a cleaning action along the cleaning trajectory. The present disclosure also discloses a cleaning apparatus, a cleaning device, and a storage medium.