基於防鎖死剎車系統輔以摩擦係數估測系統應用於智慧型輪椅

Abstract

在未來，高齡化問題將會日趨嚴重。對於醫療照護上，行動輔助載具是其中一個解決方案。常見的行動輔具主要為輪椅，而使用的安全性是一個重要課題。對於一般輪椅而言，多數皆採用固定式手煞車或裝置碟煞來提供乘坐者控制輪椅。然而煞車使用不當易造成打滑的危險，且目前尚未有將防鎖死煞車系統的概念納入輪椅之中。因此本論文將此概念套用至智慧型輪椅，目的以提升乘坐者使用輪椅的安全性。 防鎖死煞車系統中，主要包含的架構為核心演算法以及摩擦係數估測系統。系統核心以適應性模糊類神經推論系統為代表，並以陀螺儀偵測加速度與角度資訊進而對輪椅進行控制。以簡易的輪椅模型實現有效率的煞車以提升行駛安全性；摩擦係數估測主要採用粒子濾波器(Particle Filter)，應用其快速適應非線性及未知環境的特點得出當下路面的摩擦係數，亦參考相關路面的摩擦係數範圍以提供防鎖死煞車系統更精準的進行煞車控制。乘坐者只需對輪椅點選停止命令即可啟動煞車系統，實現簡易且效率的操作方式。明確減少煞車時間及距離，提升輪椅的乘坐安全。

In the future, the population’s aging problem will become increasingly serious. For medical care, action-assisted vehicles are one of the solutions. Wheelchair is a common mobility assistance equipment and the safety of the user is an important issue. For the ordinary wheelchairs, most of them use a fixed handbrake or disc brake to allow the users to stop the wheelchair. However, improper use of brakes tends to cause slippage, and there is no concept of the anti-lock braking system for the wheelchair. Therefore, this paper applies this idea to intelligent wheelchairs with the aim of enhancing the safety of users in wheelchairs. The anti-lock braking system architecture includes the core algorithms of adaptive fuzzy neural inference system and the friction coefficient estimation system. The friction coefficient estimation system uses particle filter to quickly adapt to a non-linear state and unknown environment. The system provides more accurate braking control for the anti-lock braking system according to the range of the friction coefficient based on the pavement type. In ABS, it uses the gyroscope to detect the acceleration and wheelchair angle information and then calculates the parameters of wheelchair. The user clicks the stop command on the wheelchair to activate the brake system to achieve a simple and efficient mode of operation. It can efficiently reduce the braking time, braking distance and enhance the riding safety of wheelchairs.