White Cane Detection With Pixel Masking for Mobile Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current motorized mobile systems lack the ability to safely and securely adapt to users' varying abilities, health conditions, and environments, compromising safety and independence, especially for individuals with mobility impairments or fatigue-based conditions.
Innovation Solution
A Smart Motorized Mobile System (S-MMS) with an integrated processing system and situational awareness controller that utilizes a federation of sensors for 360-degree coverage, predictive techniques, and secure communication protocols to enhance user safety and independence by providing real-time environmental awareness and adaptive control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motorized mobile systems use basic sensor arrays for navigation, then device complexity is reduced, but situational awareness precision and safety are compromised
Solution Approach 1:
The system divides the sensing task into specialized segments: white cane detectors identify cane presence, pixel masks filter cane pixels from images, and separate processing pathways handle cane-related data versus general environmental data. This segmentation allows each component to focus on specific functions, improving overall reliability without requiring a complete redesign of the entire system.
Solution Approach 2:
The patent introduces intermediary processing layers including pixel masks that act as filters between the image sensor and the main processing system. These intermediaries selectively block or pass specific pixel data based on whether it corresponds to a white cane, enabling precise cane detection without overwhelming the main system with irrelevant data.
2Measurement precision
If the system filters out white cane pixels to improve navigation accuracy, then measurement precision for obstacles is improved, but loss of information about the user's mobility aid occurs
Solution Approach 1:
The system implements feedback mechanisms where the white cane detector continuously monitors for cane presence and adjusts pixel masking in real-time. When a cane is detected, the system applies appropriate pixel masks to exclude cane pixels from obstacle detection algorithms. This feedback loop ensures that cane information is preserved for mobility assistance while preventing it from interfering with obstacle measurements.
Solution Approach 2:
The patent applies local quality by treating different regions of the image differently: pixels corresponding to the white cane receive special handling through pixel masks, while other regions are processed for general obstacle detection. This localized differentiation allows the system to maintain high measurement precision for obstacles while preserving cane information in specific image regions.
3Reliability
If the system uses comprehensive sensor arrays for 360-degree coverage, then situational awareness is improved, but device complexity and energy consumption increase
Solution Approach 1:
The system employs partial action by selectively activating and processing data from sensor arrays based on detected conditions. When a white cane is detected, the system applies pixel masks to specific regions rather than processing the entire image feed, reducing computational energy requirements while maintaining situational awareness in critical areas.
Solution Approach 2:
The sensor data processing is segmented into priority levels: white cane detection receives highest priority with dedicated processing resources, followed by general obstacle detection, and then peripheral environmental monitoring. This segmentation allows the system to maintain comprehensive situational awareness while managing energy consumption by allocating processing power dynamically based on detected conditions.
Data Source
AI summary
A processing system is for a motorized mobile system that provides powered mobility to one or more users. The processing system comprising at least one sensor that is operably configured to generate a point cloud of objects in a field-of-view of the sensors, wherein the object is identified and removed to enhance navigation or operation of the MMS.