Robot Cleaner Adaptive Driving for Obstacle-Specific Navigation
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Solution Overview
Problem
Current robot cleaners lack an efficient method to adapt their driving strategies based on different types of obstacles, which can lead to suboptimal cleaning performance and speed.
Innovation Solution
A robot cleaner equipped with a processor that identifies obstacles of different types and adjusts its driving direction and pattern accordingly, using distinct distances and maneuvers such as zigzag patterns or rotations to effectively navigate and clean around various obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot cleaner uses a uniform driving method for all obstacles, then the control logic is simple, but the cleaning performance and speed are suboptimal
Solution Approach 1:
The patent applies local quality by implementing different driving strategies for different obstacle types. The processor identifies obstacle types (e.g., walls, furniture, small objects) and applies specific driving patterns tailored to each type, such as zigzag patterns for walls and direct avoidance for small objects, thereby optimizing cleaning performance for each local situation rather than using a uniform approach
Solution Approach 2:
The patent implements dynamics by making the driving strategy adaptive and changeable based on real-time obstacle detection. The system dynamically adjusts its driving behavior by switching between different patterns (zigzag, rotation, direct avoidance) depending on the identified obstacle type, transforming a static control system into a dynamic one that responds to environmental variations
2Productivity
If the robot cleaner changes driving direction from different spaced distances for different obstacle types, then the cleaning efficiency is improved, but the sensor processing and control complexity increase
Solution Approach 1:
The patent applies segmentation by dividing obstacles into distinct categories (e.g., walls, large furniture, small objects) based on sensor data. The processor segments the cleaning space by identifying and classifying different obstacle types, then applies specific driving patterns to each segment, making the complex task of navigating diverse obstacles more manageable and efficient
3Area of stationary object
If the robot cleaner uses zigzag patterns for all obstacles, then the cleaning coverage is improved, but the cleaning speed decreases
Solution Approach 1:
The patent implements dynamics by making the driving pattern adaptive rather than static. The system dynamically selects between zigzag patterns (for high coverage along walls) and direct avoidance maneuvers (for speed when encountering small obstacles), transforming a single-speed cleaning system into a variable-speed system that adjusts its approach based on real-time obstacle identification
Data Source
AI summary
A robot cleaner is provided. The robot cleaner includes a driving unit, a memory storing a map for a space in which the robot cleaner is located, and a processor which controls the driving unit to drive the robot cleaner in a cleaning region included in the map based on information obtained through a sensor, controls the driving unit so as to identify types of obstacles located in the cleaning region while the robot cleaner drives in the cleaning region and change the driving direction of the robot cleaner at different distances for different types of obstacles.