Mobility Vehicle Wheel Route Control on Curved Surfaces
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Solution Overview
Problem
Mobility vehicles face challenges when driving on curved surfaces due to differences in wheel travel, leading to potential wheel sticking or inability to move, and existing solutions like dynamic suspension require hardware modifications, increasing costs.
Innovation Solution
A system and method that use motor control logic to adjust speed and torque of the vehicle's motor based on real-time road surface information acquired by a LiDAR and camera, generating a driving route for each wheel to navigate curved surfaces effectively without modifying the vehicle's hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic suspension is mounted to solve wheel sticking on curved surfaces, then the mobility vehicle can navigate curved surfaces better, but hardware must be changed and manufacturing cost increases
Solution Approach 1:
The patent replaces the mechanical dynamic suspension system with a motor control system that uses sensors (cameras, LiDAR) to detect road surface curvature and adjusts motor output accordingly. This substitutes complex mechanical hardware with electronic control, maintaining wheel movement reliability while avoiding hardware modifications.
Solution Approach 2:
The patent changes the control parameters of the motor (speed, torque) based on detected road surface conditions. By dynamically adjusting motor parameters according to real-time curvature detection, the system achieves adaptive wheel control without modifying the physical suspension hardware.
2Reliability
If high-performance suspension is mounted in a mobility vehicle, then the vehicle can handle curved surfaces better, but manufacturing cost excessively increases
Solution Approach 1:
The patent replaces expensive mechanical suspension hardware with a cost-effective sensor-based motor control system. This electronic control approach achieves the same functional goal of navigating curved surfaces without the high manufacturing costs associated with high-performance suspension components.
Solution Approach 2:
The patent uses relatively inexpensive sensors (cameras, LiDAR) and standard motors with advanced control algorithms, rather than expensive specialized suspension hardware. This approach provides the required performance at a fraction of the cost of high-performance mechanical suspension systems.
3Device complexity
If motor control logic is used to adjust wheel movement on curved surfaces, then hardware modifications are avoided, but real-time detection and control complexity increases
Solution Approach 1:
The patent implements a feedback control loop where sensors continuously detect road surface curvature, the controller processes this information, and motor parameters are adjusted in real-time. This automated feedback system manages the control complexity through systematic sensor-processing-actuation cycles.
Solution Approach 2:
The patent uses multi-functional sensors (cameras and LiDAR) that can detect various road conditions beyond just curvature, and the motor control system handles multiple parameters (speed, torque) simultaneously. This universal approach consolidates multiple functions into integrated systems, managing complexity through versatility.
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
Enables mobility vehicles to navigate curved surfaces efficiently by adjusting wheel movement in real-time, reducing the risk of wheel sticking and preventing vehicles from getting stuck in uneven terrain, all while maintaining existing hardware configurations.
Implementation Method 1
a front terrain scanning unit configured to detect light detection and ranging (LiDAR) point data in front of the mobility vehicle
Implementation Method 2
scan a surface image in front of the mobility vehicle
Data Source
AI summary
A system for controlling driving of a mobility vehicle may include a front terrain scanning unit configured to detect LiDAR point data and scan a surface image in front of the mobility vehicle, and a driving unit configured to provide power to move the mobility vehicle. The system may further include a controller configured to store a specification of the mobility vehicle including a dynamic radius of each wheel, generate a driving route using the LiDAR point data, detect depth data of a surface based on the surface image, acquire an actual driving route for each wheel using the depth data of the surface within the driving route for each wheel and the dynamic radius of each wheel of the mobility vehicle, generate a driving command for the actual driving route for each wheel, and control an operation of the driving unit according to the generated driving command.