Abstract
This paper presents a novel navigation and control system for autonomous mobile robots that includes path planning, localization, and control. A unique vision-based pose and velocity estimation scheme utilizing both the continuous and discrete forms of the Euclidean homography matrix is fused with inertial and optical encoder measurements to estimate the pose, orientation, and velocity of the robot and ensure accurate localization and control signals. A depth estimation system is integrated in order to overcome the loss of scale inherent in vision-based estimation. A path following control system is introduced that is capable of guiding the robot along a designated curve. Stability analysis is provided for the control system and experimental results are presented that prove the combined localization and control system performs with high accuracy.
| Original language | English |
|---|---|
| Pages (from-to) | 1237-1250 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Cybernetics |
| Volume | 43 |
| Issue number | 4 |
| DOIs | |
| State | Published - Aug 2013 |
Keywords
- Kalman filters
- Mobile robots
- Robot control
- Robot sensing systems
- Sensor fusion
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