User feedback on potential obstacles and error conditions detected by autonomous mobile robots
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous mobile robots face challenges in effectively navigating and cleaning environments due to undetected obstacles and error conditions, leading to incomplete cleaning missions and inefficient resource allocation.
Innovation Solution
The implementation of a system that allows autonomous mobile robots to detect potential obstacles and error conditions, provide user feedback mechanisms through mobile computing devices, and perform tidy-up missions based on user input, enabling more efficient cleaning operations and improved robot performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous mobile robot uses sensor-based obstacle detection, then the robot can avoid obstacles during cleaning missions, but false detections occur leading to incomplete cleaning coverage
Solution Approach 1:
The system implements a feedback loop where users provide corrections on false obstacle detections through a mobile computing device. The robot receives this feedback and updates its navigation to clean previously avoided areas, thereby improving detection reliability while maintaining cleaning productivity.
Solution Approach 2:
A mobile computing device serves as an intermediary between the robot's sensor data and the cleaning execution. It processes sensor information, presents it to the user for verification, and relays corrected navigation commands back to the robot, resolving false detections without compromising cleaning coverage.
2Reliability
If the robot avoids detected potential obstacles, then cleaning safety is improved, but cleaning coverage is reduced due to uncleaned areas
Solution Approach 1:
The obstacle avoidance behavior is made dynamic rather than static. Initially, the robot avoids detected obstacles for safety, but upon receiving user feedback confirming false detections, it dynamically updates its navigation to clean the previously avoided areas, thus optimizing both safety and coverage.
Solution Approach 2:
The system performs preliminary obstacle detection and avoidance to ensure safety during the first cleaning mission. Then, using user feedback, it performs a second cleaning mission to address previously avoided areas, ensuring complete coverage without compromising initial safety.
3Area of stationary object
If the robot performs multiple cleaning missions to cover all areas, then cleaning coverage is improved, but time and energy consumption increase
Solution Approach 1:
The system performs a preliminary cleaning mission with conservative obstacle avoidance to ensure safety. Based on user feedback from this first mission, it plans and executes a targeted second mission only for previously avoided areas, rather than performing redundant full-area cleanings, thus reducing total time and energy loss.
4Reliability
If the robot uses conservative navigation to avoid all detected obstacles, then detection reliability is improved, but cleaning efficiency decreases due to repeated visits to same areas
Solution Approach 1:
The system uses user feedback to correct false detection decisions. After conservative initial navigation based on sensor data, the feedback mechanism allows users to verify actual obstacle presence, enabling the robot to optimize its path and avoid unnecessary re-visits to already cleaned areas, thus improving efficiency while maintaining detection reliability.
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
A mobile computing device includes a user input device and a controller. The user input device includes a display, and the controller is operably connected to the user input device and configured to execute instructions to perform operations. The operations include presenting on the display, information about one or more areas that were not cleaned by an autonomous cleaning robot during a first mission. The operations further include transmitting data corresponding to a user-selected subset of the one or more areas to cause the robot to clean the user-selected subset during a second mission.