摘要
针对残疾人的前臂假肢在端水等运动过程中需要手部虎口一直与大地保持平行,即手部实现姿态自平衡问题,提出采用四元数的姿态解算算法,并采用卡尔曼滤波融合MPU6050传感器中陀螺仪和加速度计的输出数据,补偿了陀螺仪输出数据的随机漂移误差,得到前臂假肢手部姿态的正确估计。该系统由安卓手机、STM32单片机、MPU6050传感器、高性能数字舵机组成,通过安卓手机语音识别向STM32单片机发送是否保持手部自平衡指令,由STM32实时采集MPU6050中陀螺仪和加速度计的数据并经过算法处理后,通过串口向舵机发送信号。实验结果表明,这种姿态估计算法有效地解决了前臂假肢在运动过程中手部自平衡问题,为前肢缺失的残疾人提供了便利。
The forearm prosthetic hand designed for the disabled need achieve it ′ s first web keeping in parallel with the earth in the processing of movement like drinking and other actions. That is, the hand realizes the attitude self-balancing problem. Aiming at the estimation of the forearm prosthesis ′ s attitude angles, an attitude solution algorithm based on quaternion is used. Using Kalman filter to fuse the data from gyroscope and accelerometer in MPU6050, an optimal estimation for the attitude of forearm prosthesis is achieved after the compensation of the angular velocity drift error of gyroscope. The system consists of android phones,STM32 microcontroller 、 MPU6050 、 high performance of steering gear. Through the voice recognition, android mobile phone sends the instructions whether the forearm prosthetic hand need to keep the balance to STM32. Actuating signal can be send to steering gear through the serial port after data are collected and processed with algorithm from acceleration sensor and gyroscope in MPU6050 via STM32. The experimental results show that the attitude estimation algorithm is effective and the forearm prosthetic hand can keep balance during motion processes. This facilitates the disabled with the lack of the front arm.
出处
《电子技术应用》
北大核心
2016年第5期78-81,共4页
Application of Electronic Technique
基金
国家教委博士点基金(20133718110013)
山东省科技发展计划项目(2013GSF11858)
青岛民生科技计划项目"反恐防暴机器人"(13-1-3-121-NSH)
关键词
前臂假肢
姿态估计
四元数
卡尔曼滤波
the forearm prosthesis
attitude estimation
quaternion
Kalman filter