AI Rollator Navigation Using Facial Recognition and Auto-Stop
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Solution Overview
Problem
Current assistive technologies for the elderly and disabled, such as electric wheelchairs and walkers, lack the ability to autonomously recognize and self-drive to users using advanced sensors and artificial intelligence, limiting their convenience and safety.
Innovation Solution
A battery-powered, remote-controllable rollator equipped with a computer vision system utilizing deep convolutional neural networks for facial recognition and an AI algorithm to compute motion paths, enabling it to autonomously navigate and stop near the user, with features like motorized wheels, sensors, and wireless communication for remote control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional electric wheelchairs and walkers are used, then basic mobility assistance is provided, but they lack autonomous recognition and self-drive capabilities to users
Solution Approach 1:
The rollator integrates multiple functions including facial recognition, autonomous navigation, remote control, and mobility assistance into a single device. The system can operate in multiple modes: autonomous mode where it recognizes the user's face and drives to them, remote-controlled mode for assisted operation, and stationary mode for user convenience, thereby achieving multi-functionality that resolves the contradiction between automation and complexity.
Solution Approach 2:
The rollator employs self-service capabilities through facial recognition technology that automatically identifies the user and initiates autonomous navigation without requiring manual input. The system serves itself by computing motion paths and driving to the recognized user autonomously, reducing the need for complex manual control systems while maintaining high automation levels.
2Ease of operation
If advanced sensors and AI systems are added to enable autonomous recognition and self-drive, then user convenience and safety are enhanced, but device complexity increases
Solution Approach 1:
The system replaces complex mechanical control interfaces with optical and computational systems. Facial recognition using deep convolutional neural networks substitutes for manual identification processes, and autonomous navigation using sensor fusion and path computation algorithms replaces manual steering mechanisms, thereby enhancing ease of operation while managing complexity through intelligent substitution.
Solution Approach 2:
The rollator introduces an intermediary AI processing layer that mediates between the sensors and the motor control systems. This intermediary layer processes facial recognition, computes motion paths, and coordinates autonomous driving functions, simplifying the overall system architecture by centralizing intelligence while maintaining ease of operation through automated decision-making.
3Measurement precision
If the rollator autonomously navigates to the user using facial recognition, then recognition accuracy is improved, but navigation time and computational processing increase
Solution Approach 1:
The system performs preliminary actions by pre-processing facial features and pre-computing navigation paths before autonomous navigation begins. The facial recognition system prepares identification data in advance, and the path computation algorithm pre-calculates optimal routes, thereby reducing actual navigation time while maintaining high recognition accuracy through advance preparation.
Solution Approach 2:
The rollator employs periodic action through continuous facial recognition updates and real-time path re-computation during navigation. The system periodically verifies user identity and adjusts navigation paths based on environmental feedback, maintaining high recognition accuracy while optimizing navigation time through iterative, time-efficient processing cycles.
Data Source
AI summary
The present invention is a battery-powered, remote-controllable rollator with embedded computer systems and computer vision system. The present invention recognizes the user's face by using artificial intelligence technology, namely, the deep convolutional neural networks, and uses that information to localize the rollator's position in relation to the user. An artificial intelligence algorithm computes the motion path and drives the present invention to the user. The present invention can automatically stop once approached to a preset stopping distance from the user. Once stationary, the present invention can then be used by the user.