Abstract
This paper designs a control system for an automatic handling mobile robot based on s3c2440, which can recognize environment by a laser sensor. And according to the fact that the accumulative error will increase with time in inertial navigation system and steering control is easy to be out of control for heavy robot using differential steering mechanism, two effective solutions are proposed. An inertial navigation algorithm is used for the automatic control of the robot, and an active trap system, including the generation device of magnetic field and detecting device, is designed for eliminating accumulative error. In order to improve steering control precision, a motion control algorithm is presented based on gyroscope and accelerometer. The results of experiments prove the validity of the presented control algorithm, and the navigation performance is improved.
Original language | English |
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Title of host publication | 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics |
Publisher | IEEE |
Pages | 3118-3123 |
Number of pages | 6 |
ISBN (Electronic) | 9781467391047 |
DOIs | |
Publication status | Published - 28 Sept 2015 |
Externally published | Yes |
Event | 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics - Yunnan, China Duration: 8 Aug 2015 → 10 Aug 2015 |
Conference
Conference | 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics |
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Country/Territory | China |
City | Yunnan |
Period | 8/08/15 → 10/08/15 |
Keywords
- Error Correction
- Inertial Navigation
- Laser Sensor
- Mobile Robot
- Motion Stability
ASJC Scopus subject areas
- Computer Networks and Communications
- Human-Computer Interaction
- Computational Theory and Mathematics
- Control and Systems Engineering
- Computer Vision and Pattern Recognition
- Computer Science Applications