A Sensor Fusion Based Nonholonomic Wheeled Mobile Robot for Tracking Control.

Area of Science:

• Robotics
• Control Systems
• Sensor Fusion

Background:

• Nonholonomic wheeled mobile robots (NWMRs) require precise real-time trajectory tracking for various applications.
• Traditional methods using Euler angles for posture computation can suffer from gimbal lock.
• Accurate sensor data integration is crucial for reliable robot navigation and tracking.

Purpose of the Study:

• To propose a detailed design procedure for real-time trajectory tracking of NWMRs.
• To enhance posture computation accuracy by utilizing quaternions, avoiding gimbal lock.
• To integrate data from multiple sensors for robust position estimation and object tracking.

Main Methods:

• Utilizing a 9-axis micro electro-mechanical systems (MEMS) inertial measurement unit (IMU) for posture measurement.
• Employing global positioning system (GPS) for position acquisition and radio frequency (RF) module for data transmission.
• Implementing quaternion-based computation to avoid gimbal lock during posture calculation.
• Applying the Kalman filter to denoise GPS readings and estimate NWMR position for object tracking.

Main Results:

• Simulation results demonstrate that posture error converges to zero within 3.928 seconds during dynamic tracking.
• Experimental validation confirms the feasibility and effectiveness of the proposed real-time trajectory tracking system.
• The integrated system achieves accurate tracking of the NWMR relative to a hand-held device.

Conclusions:

• The proposed method effectively achieves real-time trajectory tracking for NWMRs.
• Quaternion representation and Kalman filtering significantly improve posture and position estimation accuracy.
• The system's validation through simulations and experiments highlights its practical applicability in robotics.