Robot Floorplan Mapping Using Object Movement Patterns
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Solution Overview
Problem
Existing robot navigation systems struggle to accurately map and navigate properties due to dynamic changes in lighting conditions, object permanence, and obstacle movement, leading to inefficiencies and potential collisions.
Innovation Solution
A system that generates floorplans using sensor data to detect object movement patterns, determine navigable areas, and update maps in real-time to account for lighting conditions and object permanence, incorporating confidence values for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If robot navigation systems use static maps for navigation, then the system complexity is low, but the navigation accuracy deteriorates due to dynamic changes in lighting conditions, object permanence, and obstacle movement
Solution Approach 1:
The patent applies dynamics by transitioning from static maps to dynamic floorplans that continuously update to reflect changing environmental conditions. The system monitors object permanence, lighting changes, and obstacle movements in real-time, adjusting the navigation map accordingly. This allows the robot to adapt to dynamic environments while maintaining navigation accuracy without requiring overly complex systems.
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing sensor data with the current floorplan model. When discrepancies are detected (such as moved objects or changed lighting conditions), the system updates the floorplan and adjusts navigation routes. This closed-loop feedback ensures high navigation accuracy while managing system complexity through efficient update protocols.
2Measurement precision
If the robot performs frequent localization to correct position drift, then the position accuracy is improved, but the time consumption and productivity deteriorate
Solution Approach 1:
The system performs preliminary action by pre-processing sensor data to identify stable, permanent objects in the environment before navigation begins. These pre-identified landmarks are stored in the floorplan for quick reference during localization, eliminating the need for frequent comprehensive environmental scans and improving both accuracy and efficiency.
Solution Approach 2:
The patent applies partial action by performing localization only when necessary rather than continuously. The system uses confidence values to determine when position drift has reached a threshold requiring correction, avoiding unnecessary localization operations that would consume time and reduce productivity while still maintaining sufficient position accuracy.
3Reliability
If the robot avoids all areas with moving objects to prevent collisions, then the safety is improved, but the navigable area and productivity deteriorate
Solution Approach 1:
The system applies local quality by differentiating between areas with moving objects and safe areas in the floorplan. Instead of treating all areas uniformly, the system assigns different risk levels and navigation restrictions to specific locations based on real-time object detection and permanence analysis. This allows the robot to navigate efficiently through safe areas while maintaining high collision avoidance in areas with moving objects.
Solution Approach 2:
The patent uses parameter changes by dynamically adjusting navigation parameters such as speed, distance thresholds, and route selection based on the presence and permanence of objects. When permanent objects are detected, the system maintains confident navigation; when temporary or moving objects are detected, it adjusts parameters to avoid collisions, optimizing both safety and productivity through adaptive parameter modification.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for robot navigation. In some implementations, a method includes obtaining sensor data captured by one or more sensors located at a property over a time period; detecting an object represented in the sensor data; detecting, using the detected object and multiple subsets of the sensor data, a movement pattern of the object over the time period; determining an area navigable for a robot at the property using the detected movement pattern of the object over the time period; and providing, to the robot, an indication of the area navigable for the robot.