AR Wearable Odometry With Vehicle Sensor Fusion for Safer Mobility
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Solution Overview
Problem
The integration of augmented reality (AR) wearable devices with personal mobility systems (PM systems) aims to address the safety risks and operational challenges posed by the lack of performance feedback indicators and obstacle detection in PM systems, particularly in urban environments where user concentration and training are critical for safe operation.
Innovation Solution
AR wearable devices communicate with PM systems to centralize telemetry data, detect physical obstacles, and interact with virtual objects, modulating the PM system's performance by providing users with real-time feedback and enhancing navigation through augmented reality overlays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If AR wearable devices are integrated with PM systems to provide real-time feedback and obstacle detection, then user safety and operational awareness are improved, but device complexity and cognitive burden increase
Solution Approach 1:
The system divides functionality between the PM system (which collects sensor data from motors, sensors, and controllers) and the AR wearable device (which processes and displays augmented reality information). This segmentation allows safety features to be added without significantly complicating the core PM system architecture.
Solution Approach 2:
The AR wearable device acts as an intermediary that receives data from the PM system, processes it, and presents it to the user in an augmented reality format. This intermediary role enables comprehensive safety monitoring without requiring direct complexity in the PM system itself.
2Loss of information
If additional controls and performance indicators are incorporated into PM systems, then user feedback and performance monitoring are improved, but ease of operation deteriorates due to increased complexity
Solution Approach 1:
The system replaces traditional mechanical indicators (LEDs, LCD displays on the PM system) with an optical/digital display in the AR wearable device. This substitution allows comprehensive performance feedback to be delivered without adding physical controls or indicators to the PM system, maintaining operational simplicity.
Solution Approach 2:
The system moves the display interface from the physical PM system to the user's visual field through augmented reality overlays. This dimensional shift from physical controls to virtual overlays provides comprehensive information without occupying physical space on the PM system, preserving ease of operation.
3Measurement precision
If sensor fusion is performed between AR wearable device and PM system, then measurement precision and pose determination are improved, but use of energy and data processing requirements increase
Solution Approach 1:
The system merges sensor data from the PM system (motor encoders, inertial sensors, controller data) with visual data from the AR wearable device cameras. This combination improves pose determination accuracy by fusing multiple data sources, while the distributed architecture allows energy-intensive processing to occur in the AR device rather than the PM system.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This integration reduces the cognitive burden on users by providing real-time feedback and enhancing safety through obstacle detection and performance modulation, improving the overall user experience and reducing accidents in dynamic urban environments.
Implementation Method 1
an inertial measurement unit (IMU) sensor of the personal mobility system
Implementation Method 2
determining pose information of the AR wearable device using a visual-inertial odometry algorithm based on images captured by a camera of the AR wearable device and data from the IMU sensor
Data Source
AI summary
A method of providing an interactive personal mobility system, performed by one or more processors, comprises determining an initial pose by visual-inertial odometry performed on images and inertial measurement unit (IMU) data generated by a wearable augmented reality device. Sensor data transmitted from a personal mobility system is received, and sensor fusion is performed on the data received from the personal mobility system to provide an updated pose. Augmented reality effects are displayed on the wearable augmented reality device based on the updated pose.