Control of autonomous mobile robots
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Solution Overview
Problem
Autonomous mobile robots face inefficiencies in cleaning tasks due to lack of targeted cleaning strategies, often failing to prioritize dirtier regions effectively, especially in time-constrained missions or with limited energy.
Innovation Solution
Implementing behavior control zones that allow users to prioritize cleaning regions based on sensor data and user input, enabling the robot to focus on dirtier areas first and adjust cleaning parameters like suction power and movement speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the robot cleans the entire floor surface, then the cleaning coverage is maximized, but the cleaning time and energy consumption increase beyond available resources
Solution Approach 1:
The patent segments the cleaning environment into multiple zones with different priority levels (high-priority zones and low-priority zones). The robot performs cleaning operations in a staged manner, first completing high-priority zones within the time constraint, and optionally proceeding to low-priority zones if time and energy remain. This segmentation allows the robot to maximize cleaning coverage within available time by focusing on important areas first.
Solution Approach 2:
The patent implements preliminary action by having the robot perform a mapping run before the actual cleaning mission. During this preliminary mapping run, the robot collects occupancy data and identifies high-priority zones that should be cleaned first. This advance preparation enables the robot to optimize its cleaning path and prioritize areas, ensuring maximum cleaning coverage within the time constraint without wasting time on low-priority areas.
2Productivity
If the robot increases suction power to clean dirtier regions faster, then cleaning efficiency improves, but energy consumption increases
Solution Approach 1:
The patent applies local quality by adjusting cleaning parameters dynamically based on the specific zone being cleaned. When the robot enters high-priority zones, it increases suction power to clean more effectively and quickly. When in low-priority zones or transitioning between zones, the robot reduces suction power to conserve energy. This localized adjustment of cleaning intensity optimizes the balance between cleaning efficiency and energy consumption.
Solution Approach 2:
The patent implements dynamics by making cleaning parameters adaptive rather than static. The robot continuously monitors its location, remaining time, and energy levels, and dynamically adjusts suction power and movement speed accordingly. This dynamic adjustment allows the robot to maintain high cleaning efficiency in critical areas while conserving energy for when it needs to complete additional zones or return to the charging station.
3Productivity
If the robot prioritizes multiple behavior control zones simultaneously, then comprehensive cleaning is achieved, but the robot becomes unable to complete any zones within time constraints
Solution Approach 1:
The patent segments the set of behavior control zones into priority groups (high-priority and low-priority zones). Instead of treating all zones equally, the robot processes high-priority zones first within the time constraint, ensuring that the most important areas are cleaned thoroughly. Low-priority zones are addressed only if time and energy remain after completing high-priority zones. This segmentation enables the robot to achieve meaningful cleaning throughput within time constraints.
Solution Approach 2:
The patent applies partial action by having the robot focus on completing a subset of high-priority zones rather than attempting to clean all zones equally. The robot performs thorough cleaning in the most important areas (high-priority zones) and may perform partial or reduced cleaning in lower-priority areas if time permits. This approach ensures that critical cleaning needs are met within time constraints, achieving productive results rather than spreading resources too thin across all zones.
Data Source
Figure 1
Figure 2
Figure 3A
AI summary
A method includes receiving mapping data collected by an autonomous cleaning robot as the autonomous cleaning robot moves about an environment. A portion of the mapping data is indicative of a location of an object in the environment. The method includes defining a clean zone at the location of the object such that the autonomous cleaning robot initiates a clean behavior constrained to the clean zone in response to encountering the clean zone in the environment.