Exploration of an unknown environment by an autonomous mobile robot
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Solution Overview
Problem
Autonomous mobile robots face inefficiencies in exploring and mapping unfamiliar environments, often moving back and forth between rooms due to lack of effective strategies for dividing the operational area into sub-areas, leading to time and energy wastage.
Innovation Solution
The robot employs a method to explore a room completely before moving to the next, using sensor data to detect obstacles and hypothesize sub-areas, with hypotheses tested for plausibility and user feedback, and subdividing the map into rectangular areas based on assumptions of rectangular room shapes, ensuring efficient exploration and user-intuitive division.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot moves randomly or uses simple exploration methods, then the robot can cover the area, but it moves back and forth between rooms causing time and energy waste
Solution Approach 1:
The patent divides the operational area into multiple sub-areas (rooms) based on detected boundaries such as doors and walls. The robot then systematically explores each sub-area individually rather than moving randomly throughout the entire area, which eliminates unnecessary back-and-forth travel between rooms and improves exploration efficiency.
2Reliability
If the robot creates a detailed map of the environment, then the robot can navigate better, but the robot needs to explore every area which increases time consumption
Solution Approach 1:
The patent creates maps for each sub-area separately after the robot has explored that specific sub-area. This segmented mapping approach allows the robot to build accurate local maps without needing to explore the entire environment simultaneously, reducing total exploration time while maintaining navigation reliability within each sub-area.
Solution Approach 2:
The robot performs boundary detection and sub-area identification before conducting detailed exploration and mapping of each sub-area. By preliminarily dividing the environment into manageable sub-areas based on detected boundaries, the robot prepares an exploration structure that reduces time consumption while ensuring reliable navigation within each defined sub-area.
3Productivity
If the robot divides the area into sub-areas, then the robot can explore more systematically, but the robot needs to detect boundaries and hypothesize sub-areas which increases system complexity
Solution Approach 1:
The robot uses its own sensor data and movement information to automatically detect boundaries and hypothesize sub-areas without requiring external assistance or complex pre-programmed environmental models. The system serves itself by utilizing the data already collected during normal operation to perform segmentation, reducing the need for additional complex detection hardware or systems.
Data Source
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AI summary
The invention relates to a method for exploring a robot area of application by an autonomous mobile robot. According to one mode of embodiment, the method comprises starting an exploratory journey, during which the robot detects objects in the environment thereof and stores detected objects as map data on a map, while the robot moves through the robot area of application. During the exploratory journey, the robot carries out sub-area detection based on the stored map data, at least one reference sub-area being detected. It is then checked whether the reference sub-area has been fully explored. The robot repeats the sub-area detection in order to update the reference sub-area and checks again whether the (updated) reference sub-area has been fully explored. The exploration of the reference sub-area is continued until the checking process indicates that the reference sub-area has been fully explored. The robot then continues the explorative journey in another sub-area if another sub-area has been detected, the other sub-area being used as a reference sub-area.