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This paper introduces a novel hardware system structure and systematic digital signal processing algorithms for the automatic localization of an autonomous mobile robot by merging dead-reckoning and ultrasonic measurements. The multisensorial dead-reckoning (DR) subsystem is based on optimal filtering that merges heading readings from a magnetic compass, a rate-gyroscope, and two encoders mounted on the robot wheels to compute the dead-reckoned location estimate. The novel ultrasonic localization subsystem consists of one ultrasonic transmitter and one radio-frequency (RF) controlled switch mounted at a known location fixed to an inertial frame of reference, four ultrasonic receivers, and one RF controlled switch installed on the mobile robot. Four ultrasonic time-of-flight (TOF) measurements together with the dead-reckoned location information are used to update the vehicle's position by utilizing the extended Kalman filtering (EKF) algorithm. The proposed algorithms are implemented using a host PC 586 computer and standard C++ programming techniques. The system prototype together with the experimental results were used to confirm that the system not only retains high accuracy and magnetic interference immunity, but also provides a simple and practical structure for use and installation/calibration.
Ching‐Chih Tsai (Thu,) studied this question.