Camera-Based E-Pallet Bank Angle Control for Rollover Prevention
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Solution Overview
Problem
Current e-pallet control methods are inadequate for preventing rollover, especially on non-level surfaces and during cornering maneuvers, as they rely on manual operation and lack effective feedback mechanisms to adjust speed and yaw rate accordingly.
Innovation Solution
The system employs cameras to determine the relative orientation of the user and the e-pallet, calculating a bank angle by comparing the e-pallet vertical vector with the user vertical vector, and takes control actions such as adjusting speed and yaw rate to maintain safety thresholds, using machine learning algorithms for key point detection and reliability checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual control methods are used for e-pallet operation, then ease of operation is maintained, but rollover prevention capability deteriorates due to lack of automated safety mechanisms
Solution Approach 1:
The system continuously captures images of the user, detects key points (head, shoulders, hips), calculates orientation angles, and compares them against safety thresholds to dynamically adjust e-pallet speed and prevent rollover. This closed-loop feedback mechanism automatically monitors user posture and environmental conditions, providing reliable rollover prevention without requiring complex manual intervention systems.
Solution Approach 2:
The e-pallet system autonomously monitors its own operational safety by using onboard cameras and processors to detect user orientation, calculate bank angles, and automatically adjust speed based on detected risks. The system serves itself by independently identifying hazards and implementing corrective actions without external intervention, improving reliability while keeping the control interface simple.
2Reliability
If automated control systems are implemented to prevent rollover, then safety is improved, but ease of operation deteriorates due to reduced manual control
Solution Approach 1:
The control system dynamically adjusts e-pallet operation based on real-time user orientation detection. When the user's orientation indicates potential rollover risk (e.g., excessive bank angle detected through key point analysis), the system automatically reduces speed or halts movement. This dynamic response maintains safety thresholds while preserving manual control flexibility, as the system only intervenes when necessary rather than restricting all manual operations.
3Measurement precision
If real-time camera-based monitoring is used to calculate bank angle, then rollover detection accuracy is improved, but device complexity increases due to additional sensors and processing
Solution Approach 1:
The system uses the user's body orientation as an intermediary to indirectly measure bank angle. Instead of directly measuring the e-pallet's tilt angle with complex sensors, the camera captures the user's posture (head, shoulders, hips key points), calculates their orientation relative to gravity, and infers the bank angle from this intermediate measurement. This approach achieves high measurement precision using a relatively simple camera-based system rather than complex direct measurement sensors.
4Reliability
If continuous bank angle calculation is performed using camera data, then rollover detection reliability is improved, but energy consumption increases due to constant processing
Solution Approach 1:
The system performs rapid, continuous bank angle calculations by efficiently processing camera frames and detecting key points. Rather than performing lengthy computations, the processor uses optimized algorithms to quickly identify user orientation and calculate bank angles in real-time. This rushing through computations maintains high detection reliability while minimizing energy consumption per calculation cycle, allowing continuous monitoring without excessive power draw.
Data Source
AI summary
Methods and systems for reducing the likelihood of rollover for an e-pallet are provided. The systems include one or more cameras configured to obtain camera data as to a user of the e-pallet, and a processor coupled to the one or more sensors and configured to at least facilitate determining, using the camera data, a relative orientation of the user, determining an e-pallet vertical vector based on the camera data and a user vertical vector based on the relative orientation of the user, determining a bank angle of the e-pallet based on the e-pallet vertical vector and the user vertical vector, and taking a control action for the e-pallet, in accordance with instructions provided by the processor, based on the bank angle.