摘要
An indoor positioning method for robots is presented to improve the precision of displacement measurement using only low-cost inertial measurement units(IMUs).Firstly,a high-fidelity displacement estimation for linear motion is proposed.A new robot motion model is designed as well as an axis alignment that only uses a single axis of the accelerometer.The integral error of velocity is eliminated by a new subsection calculation method.Two complementary IMUs are combined by assigning them different weights to obtain high accuracy displacement results.Secondly,an orientation estimation based on a fusion filter for the steering motion is proposed.Experiments show that the proposed method significantly improves the accuracy of linear motion measurement and is effective for the indoor positioning of a robot.
An indoor positioning method for robots is presented to improve the precision of displacement measurement using only low-cost inertial measurement units (IMUs). Firstly, a high-fidelity displacement estimation for linear motion is proposed. A new robot motion model is designed as well as an axis alignment that only uses a single axis of the accelerometer. The integral error of velocity is eliminated by a new subsection calculation method. Two complementary IMUs are combined by assigning them different weights to obtain high accuracy displacement results. Secondly, an orientation estimation based on a fusion filter for the steering motion is proposed. Experiments show that the proposed method significantly improves the accuracy of linear motion measurement and is effective for the indoor positioning of a robot. © 2017, Science Press. All right reserved.
出处
《机器人》
EI
CSCD
北大核心
2017年第3期316-323,共8页
Robot
基金
National Natural Science Foundation of China(61375103,61533004,61320106012,and 61321002)
the 863 Program of China(2014AA041602,2015AA042305 and 2015AA043202)
the Key Technologies Research and Development Program(2015BAF13B01 and 2015BAK35B01)
the Beijing Municipal Science and Technology Project(D161100003016002)
the "111" Project under Grant B08043
