Robot Map Sectoring With Human-Centric Zone Boundaries
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Solution Overview
Problem
Existing autonomous mobile robots struggle to sector their operation area in a way that is intuitive and adaptable to human users, as current methods fail to consider human-centric characteristics, leading to complex and user-unfriendly map representations.
Innovation Solution
The method involves detecting obstacles and boundary lines using sensors, generating hypotheses about zone borders and functions, and dynamically sectoring the area into zones based on user input, with the ability to adjust and refine sectoring based on user feedback and environmental characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the area is sectored into uniform zones of predefined shape and size, then the processing procedure is standardized and simple, but the result is not understandable or intuitive for human users
Solution Approach 1:
The patent applies dynamics by making the sectoring methodology adaptable rather than fixed. The system dynamically adjusts sectoring strategies based on user feedback and environmental characteristics, transitioning from static uniform zones to dynamic human-centric sectors that evolve with user interaction and learning.
Solution Approach 2:
The patent changes parameters by modifying sectoring criteria from geometric uniformity to human-understandable characteristics. It adjusts sector boundaries, shapes, and groupings based on environmental features and user preferences, transforming the parameter set from predefined geometric constraints to adaptive semantic categories.
2Productivity
If abstract sectoring methods are used to simplify path planning, then the robot's movement through the area is optimized, but the sectoring does not consider human environment characteristics and appears difficult to understand
Solution Approach 1:
The patent introduces an intermediary layer between abstract path planning and human understanding. This intermediary consists of semantically meaningful sector labels and descriptions that bridge the gap between efficient robot navigation paths and human-comprehensible environment representation, allowing both goals to coexist.
Solution Approach 2:
The patent implements feedback mechanisms where user responses to sector representations are collected and used to refine future sectoring. This feedback loop allows the system to learn which sectoring approaches users find understandable while maintaining path planning efficiency, continuously adapting to user preferences.
3Ease of operation
If the map is made more detailed and readable for humans, then user understanding improves, but the complexity of map compilation and processing increases
Solution Approach 1:
The patent applies segmentation by dividing the complex map processing task into manageable components: obstacle detection, boundary line identification, sector formation, and semantic labeling. This segmentation allows detailed human-readable maps to be created through a series of simpler processing stages rather than a single complex operation.
Data Source
AI summary
An optical triangulation sensor for distance measurement is described herein. In accordance with one embodiment, the apparatus comprises a light source for the generation of structured light, an optical reception device, at least one attachment element and a carrier with a first groove on a lateral surface of the carrier, wherein the light source and/or optical reception device is at least partially arranged in the first groove and is held in place on the carrier by the attachment element.