Sensor Fusion-Based Attitude Estimation Using Low-Cost MEMS-IMU for Mobile Robot Navigation
Recently, many low-cost micro electro mechanical systems (MEMS) IMUs have emerged for only several hundred US dollars. In comparison to high-end IMUs, an entire Inertia! Navigation System (INS) can be implemented with smaller size/volume, lower weight and costs. On the other hand, they have a relatively lower accuracy due to their larger systematic errors, such as bias, scale factor and drift, which highly depend on disturbance and temperature. Consequently, the original signal output of Tow-cost IMU must be processed to reconstruct smooth attitude estimation. For the application of mobile robot navigation, the algorithms need to be run on embedded processors with low memory and processing resources. This paper analyses various error sources in the attitude measurement for Mobile Robot using low-cost MEMS-IMU and discusses how to improve measurement accuracy by minimising the errors and optimising fusion algorithms. It presents the following aspects: investigating a cheap open source MEMS-IMU, enhancing ADC resolution by oversampling and averaging, Altering the noise caused by vibration, improving attitude estimation using sensor fusing.
Lu Lou Xin Xu Juan Cao Zhili Chen Yi Xu
College of Information Science and Engineering Chongqing Jiaotong University, Chongqing, China, 4000 Library of Chongqing Jiaotong University Chongqing, China, 400074 Faculty of Information and Control Engineering Shenyang Jianzhu University, Shenyang, China, 110168
国际会议
重庆
英文
968-971
2011-08-20（万方平台首次上网日期，不代表论文的发表时间）