Adaptive Powered Seat Control for User-Aware Mobility Safety
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Solution Overview
Problem
Current motorized mobile systems lack the ability to adapt to individual users' varying physiological and cognitive abilities, leading to inadequate safety, security, and social independence, as they are not designed to consider users' unique needs and health conditions effectively.
Innovation Solution
The integration of advanced software and hardware systems, including sensors for situational awareness, user monitoring, and communication technologies, along with human-machine interfaces, to create a secure and adaptive control system that provides personalized mobility solutions for users with diverse abilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If motorized mobile systems use standardized control systems, then device complexity is reduced and ease of manufacture is improved, but adaptability to individual users' varying physiological and cognitive abilities deteriorates
Solution Approach 1:
The control system dynamically adapts to individual users by adjusting operational parameters based on detected user characteristics. The system transitions from a static, standardized configuration to a dynamic one that modifies its behavior in real-time according to the user's physiological and cognitive abilities, thereby achieving adaptability without requiring completely different systems for each user.
Solution Approach 2:
The system changes operational parameters such as speed limits, acceleration rates, and control sensitivity based on detected user attributes. By modifying these parameters dynamically, the system accommodates varying user capabilities while maintaining a single standardized hardware platform, thus resolving the contradiction between adaptability and complexity.
2Reliability
If motorized mobile systems integrate advanced sensors and monitoring systems, then user safety and situational awareness are improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The integrated sensor system serves multiple functions simultaneously: detecting user presence, monitoring physiological states, assessing environmental conditions, and determining control parameters. This multi-functionality allows the system to achieve high reliability and safety without proportionally increasing complexity, as a single sensor array performs diverse safety-critical tasks.
Solution Approach 2:
The patent combines multiple monitoring functions into a unified control system that processes sensor data from various sources (proximity sensors, user monitoring sensors, environmental sensors) through a single integrated processor. This merging of functions reduces the overall system complexity compared to having separate dedicated systems for each monitoring task.
3Ease of operation
If motorized mobile systems provide personalized mobility solutions, then user independence and social inclusion are improved, but device complexity and customization requirements increase
Solution Approach 1:
The system automatically detects user characteristics and configures optimal operational parameters without requiring manual customization or technical intervention. The motorized mobile system performs self-adjustment based on sensor data, enabling personalized mobility solutions while eliminating the complexity of manual configuration and customization processes.
Solution Approach 2:
The system pre-configures operational parameters based on detected user attributes before the user begins operation. By performing the customization action in advance automatically, the system enables ease of operation and user independence without exposing the user to the complexity of customization settings.
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 comprises at least one sensor to measure one or more kinematic states of an object proximate to the motorized mobile system and at least one processor to use at least one object kinematic model as at least one state estimator. The at least one processor predicts a first kinematic state estimate of the object at a first time based on a prior knowledge of state for the object and a measured kinematic state observed by the sensor at a second time to determine a second kinematic state estimate of the object at the second time. The at least one processor outputs the first kinematic state estimate at the first time from the object kinematic model for use by at least one other process of the motorized mobile system.