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Research into Kinect/Inertial Measurement Units Based on Indoor Robots
Huixia Li1,2, Xi Wen3, Hang Guo4
1Institute of Space Science and Technology, Nanchang University, Nanchang 330031, China. hxli0601@gmail.com.
This study introduces an integrated robot navigation system using Kinect and Inertial Measurement Unit (IMU) to enhance indoor positioning accuracy. The combined approach significantly improves robot movement precision and stability for reliable navigation.
Area of Science:
- Robotics
- Computer Vision
- Sensor Fusion
Background:
- Indoor mobile navigation faces challenges with low positioning accuracy and cumulative errors.
- Existing systems often struggle to provide reliable real-time location data.
Purpose of the Study:
- To develop an integrated location system for robots to overcome indoor navigation limitations.
- To enhance the accuracy and stability of robot positioning using sensor fusion.
Main Methods:
- Utilized Kinect for stereo image analysis to determine robot attitude and translation via the absolute orientation algorithm.
- Integrated data from a strap-down Inertial Measurement Unit (IMU).
- Applied Kalman filtering to fuse Kinect and IMU data, optimizing position and attitude estimation and correcting errors.
Main Results:
- The proposed integrated system demonstrated improved positioning accuracy for indoor mobile robots.
- Experimental results confirmed enhanced stability in robot navigation.
- The fusion of visual odometry and IMU data effectively mitigated cumulative errors.
Conclusions:
- The integrated Kinect and IMU system offers a robust solution for accurate indoor mobile robot navigation.
- Kalman filtering is effective in correcting position and attitude errors for enhanced performance.
- This approach significantly advances the reliability of autonomous indoor robot systems.
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