Abstract
Binocular stereovision–based positioning and inertial measurement–based positioning have their respective limitations. Asynchronous fusion of a binocular vision system and an inertial navigation sy...
Highlights
Research on robot positioning is of great importance
It can be seen that the red trajectory of the integrated system is the closest to the true path, and the positioning errors of the blue trajectory from inertial navigation system (INS) alone are larger than the red trajectory from the integrated system
The results prove that the proposed algorithm can improve the positioning accuracy of a mobile robot and can limit its velocity within a certain range
Summary
Research on robot positioning is of great importance. It is impossible for a robot to establish a feedback regulator for motion control or navigation without positioning and orientation information. Traditional positioning methods commonly include the use of a global positioning system (GPS),[1] an odometer,[2] and/or an inertial measurement unit (IMU).[3] These key technologies can be found in autonomous navigation,[4] motion planning,[5] and simultaneous localization and mapping (SLAM).[6]. As one of the popular localization methods, GPS is widely used for land vehicle positioning, the signal propagated by a satellite may experience discontinuity and blockage caused by high-rise buildings or other obstacles. An IMU can provide angular velocity and specific force during inertial measurement navigation,[7] and it calculates the position and attitude information through integration. An IMU is susceptible to environment noise that can lead to the drift of positioning results over
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