This technology is a fuzzy logic-based control mechanism that calculates autonomous driving control values by combining positive fuzzy rules for target tracking with negative fuzzy rules for obstacle avoidance. It determines the optimal movement direction (avoidance angle) by applying Gaussian membership functions to obstacle location data detected by ultrasonic sensors and target point information input from a controller.
Conventional remote robot control systems rely on manual user operation, posing a high risk of collision if obstacles are not detected. Furthermore, the lack of integrated autonomous avoidance control technology reduces the reliability of remote operation.
This technology configures a control system that uses the distance and angle between the robot and the target point, as well as the robot and obstacles, as input variables. It applies positive and negative rules respectively, derives the fitness of each input fuzzy set based on mathematical formulas, and calculates the final movement avoidance angle through the computation of output fuzzy set fitness including additive offsets. Applicable to rehabilitation training, gait assistance, and medical/welfare services, it enables self-regulated obstacle avoidance, thereby enhancing the reliability of remote control in robot navigation.
This invention was developed with support from the Ministry of Education, Science and Technology's Biomimetic Robot Technology Development program.
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