Autonomous Floor Cleaner Zero-Radius Turn for Trapped Condition Exit
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Solution Overview
Problem
Autonomous floor cleaners often get trapped in small areas due to obstacle density, size, and orientation, leading to inefficient cleaning and battery waste from frequent collisions.
Innovation Solution
The autonomous floor cleaner performs a zero-radius turn while taking readings with distance sensors to determine a heading for exiting trapped conditions and navigating through occupiable spaces, allowing it to avoid obstacles and plan effective cleaning paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous floor cleaner moves randomly about the surface, then it can clean the floor surface, but it becomes trapped in small areas due to obstacle density and orientation
Solution Approach 1:
The system performs preliminary actions by executing zero-radius turns and sensor scans before attempting to exit trapped conditions. The controller proactively searches for occupiable spaces by rotating the housing and analyzing sensor data in advance, rather than reacting only after becoming stuck.
Solution Approach 2:
The system dynamically adapts its movement strategy by transitioning from random driving to structured zero-radius turns when trapped conditions are detected. The controller continuously monitors sensor input and adjusts the cleaning path in real-time, changing from linear motion to rotational motion to navigate around obstacles.
2Adaptability or versatility
If the autonomous floor cleaner bounces frequently off obstacles, then it attempts to navigate around them, but it wastes battery life
Solution Approach 1:
The system performs preliminary scanning using sensors during zero-radius turns to identify occupiable spaces before committing to movement directions. This prevents futile bouncing attempts and directs energy toward productive cleaning paths.
Solution Approach 2:
The controller continuously monitors sensor input during zero-radius turns and uses this feedback to determine the best exit direction. The system adjusts its path based on real-time obstacle detection, avoiding repeated collisions and optimizing energy usage.
3Productivity
If the autonomous floor cleaner gets stuck in small areas, then it cannot clean new floor areas, but increasing sensor analysis complexity increases device complexity
Solution Approach 1:
The controller divides the cleaning task into distinct phases: normal random driving, trapped condition detection, zero-radius turn execution, and exit path selection. Each phase has simplified control logic, making the overall system manageable despite its adaptive capabilities.
Solution Approach 2:
The system dynamically switches between different operational modes based on sensor input. When not trapped, it uses simple random driving logic. When trapped, it transitions to a structured zero-radius turn routine with sensor analysis, then returns to normal operation after exiting.
Data Source
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AI summary
An autonomous floor cleaner includes multiple occupiable space sensors for position and/or proximity sensing. Data from the occupiable space sensors can be used determine areas of occupiable space in proximity to the autonomous floor cleaner. Methods for exiting a trapped condition, obstacle avoidance, and path planning are disclosed.