| Research Abstract |
As a study of behavior learning of mobile robots, a genetic path planning algorithm with limited directional movements and a sensor fusion based tracking control scheme were examined. The control scheme is simple and efficient enough to be used in real time, and it makes the sensor fusion network learn relations between the planned path, the robot movement, and the sensor signals. Straight-line and circular movements on black-striped markers were used for teaching the network, where the internal sensors are fused with the external sensors. The preliminary experiments explain relations between the robot movement and the sensor outputs. The experimental results show the effectiveness of the proposed measurement system using the infrared photo reflectors and the gyro sensor, and also the feasibility of the learning method for the sensor fusion network. A microcontroller network based modular control system was proposed, and its performance using a serial bus was experimentally evaluated. A space-division infrared optical communication system was proposed as a method of local inter-robot communication. The communication system uses a set of modules, or transceivers, which is arranged in the circumference of the robot body. Each module detects the angle of incidence of infrared rays. Space-division communication networks can be created, because a robot can communicate with more than one robot through different modules at the same time. Hardware realization and performance measurements show that 1) communication connections between robots are maintained without interruptions when they are moving, 2) the direction of other robots can be detected with an accuracy of ±5°.
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