Dong W. Kim

Advanced Fuzzy Potential Field Method for Mobile Robot Obstacle Avoidance

An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed. The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts. The design of a fuzzy controller—advanced fuzzy potential field method (AFPFM)—that models and enhances the conventional potential field method is proposed and discussed. This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.

Genetic algorithm based robot posture

Robot-posture with genetic algorithm is presented in this paper. As a robot platform walking biped robot is used. To cope with the difficulties and explain unknown empirical laws in the robot, practical robot walking on a descending sloped floor is modeled by genetic architecture. These results from the modeling strategy is analyzed and compared.

Study on whole body motion planner of humanoid robot

In this paper, whole-body motion planner of humanoid robot based on real time path planner and self-collision detection is proposed.

Advanced Interval Type-2 Fuzzy Sliding Mode Control for Robot Manipulator

In this paper, advanced interval type-2 fuzzy sliding mode control (AIT2FSMC) for robot manipulator is proposed. The proposed AIT2FSMC is a combination of interval type-2 fuzzy system and sliding mode control. For resembling a feedback linearization (FL) control law, interval type-2 fuzzy system is designed. For compensating the approximation error between the FL control law and interval type-2 fuzzy system, sliding mode controller is designed, respectively. The tuning algorithms are derived in the sense of Lyapunov stability theorem. Two-link rigid robot manipulator with nonlinearity is used to test and the simulation results are presented to show the effectiveness of the proposed method that can control unknown system well.

Use of Genetic Algorithm for Robot-Posture

Robot-posture with genetic algorithm is presented in this paper. As a robot platform walking biped robot is used. To cope with the difficulties and explain unknown empirical laws in the robot, practical robot walking on a descending sloped floor is modeled by genetic architecture. These results from the modeling strategy is analyzed and compared.