Mobile Robot Navigation using Optimized Fuzzy Controller by Genetic Algorithm

Ran Zhao,Dong Hwan Lee,Hong Kyu Lee 한국지능시스템학회 2015 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.15 No.1

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

Intelligent Navigation for Multiple Mobile Robots with Dynamic Obstacles

Ran Zhao(조연),Hong-Kyu Lee(이홍규) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.9

This paper addresses a navigation problem for multiple mobile robots in unknown dynamic environments. The environments are completely unknown to the robots and the surrounding environments should be detected by the proximity sensors installed on the robots’ bodies. To guide the robot’s movement along collision-free paths and reach the goal positions, an intelligent navigation method based on the combination of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensor data is used to avoid small convex obstacles or other robots. Furthermore, a wall-following strategy is designed to address the special situations involving large convex or concave obstacles. Finally, when there is no collision risk, the robots will be guided toward the corresponding targets according to a target positioning strategy. All these strategies are achieved using fuzzy logic controllers, and are uniformly applied to each robot. The simulation verified that the proposed method has encouraging effectiveness for solving the navigation problem.

Fuzzy Logic Based Navigation for Multiple Mobile Robots in Indoor Environments

Zhao, Ran,Lee, Dong Hwan,Lee, Hong Kyu Korean Institute of Intelligent Systems 2015 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.15 No.4

The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots' bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors' data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the "infinite repetition" or "dead cycle" situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.

Fuzzy-based Path Planning for Multiple Mobile Robots in Unknown Dynamic Environment

Zhao, Ran,Lee, Hong-Kyu The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.12 No.2

This paper presents a path planning problem for multi-robot system in the environment with dynamic obstacles. In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly, a navigation method based on fuzzy logic controllers has been developed by using proximity sensors. There are two kinds of fuzzy controllers developed in this work, one is used for obstacle avoidance and the other is used for orientation to the target. Both static and dynamic obstacles are included in the environment and the dynamic obstacles are defined with no type of restriction of direction and velocity. Here, the environment is unknown for all the robots and the robots should detect the surrounding information only by the sensors installed on their bodies. The simulation results show that the proposed method has a positive effectiveness for the path planning problem.

Autonomous Navigation of a Mobile Robot in Unknown Environment Based on Fuzzy Inference

Ran Zhao,Dong-Hwan Lee,Hong-Kyu Lee 한국산학기술학회 2016 한국산학기술학회논문지 Vol.17 No.3

본 논문은 다양한 형태의 방해물에 대한 정보를 알 수 없는 미지의 환경에서 자율이동 로봇의 항법에 관한 제안을 하고 있다. 로봇의 이동에 따른 주변의 정보는 로봇에 부착되어 있는 근접센서를 통하여 감지하고, 충돌을 피하고 목적지에 가능한 한 빨리 도착할 수 있는 경로로 유도하기 위하여 퍼지추론에 기반 한 항해방법을 개발하였다. 여기에서 방해물들은 정지되어 있고 정형화된 경우와 비정형화된 형태들이 고려되었으며 미로와 U형태의 계곡으로 구성된 예리한 방해물들을 특별히 포함하고 있다. 벽을 따라 이동하는 방법 또한 제안하고 있으며 모의실험을 통하여 제안하고 있는 방법이 이동로봇의 항법문제를 해결하는 효과적인 방법이 된다는 것을 증명하였다. This paper presents a navigation problem for an autonomous mobile robot in an unknown environment. The environment contains various types of obstacles and is completely unknown to the robot. Therefore, all of the surrounding information must be detected by the robot's proximity sensors. A navigation method was developed based on a fuzzy inference system to guide the robot to move along a collision-free path and reach the goal position quickly. The obstacles are assumed to be static, and both regular and irregular types of obstacles were investigated. A wall following method is also proposed for a special environment that contains a labyrinth or sharp U-valley obstacles. Simulation results demonstrate that the proposed method has great potential for this navigation problem.

Fuzzy-based Path Planning for Multiple Mobile Robots in Unknown Dynamic Environment

Ran Zhao,Hong-Kyu Lee 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.2

This paper presents a path planning problem for multi-robot system in the environment with dynamic obstacles. In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly, a navigation method based on fuzzy logic controllers has been developed by using proximity sensors. There are two kinds of fuzzy controllers developed in this work, one is used for obstacle avoidance and the other is used for orientation to the target. Both static and dynamic obstacles are included in the environment and the dynamic obstacles are defined with no type of restriction of direction and velocity. Here, the environment is unknown for all the robots and the robots should detect the surrounding information only by the sensors installed on their bodies. The simulation results show that the proposed method has a positive effectiveness for the path planning problem.

Fuzzy Logic Based Navigation for Multiple Mobile Robots in Indoor Environments

Ran Zhao,Dong Hwan Lee,Hong Kyu Lee 한국지능시스템학회 2015 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.15 No.4

The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots’ bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors’ data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the “infinite repetition” or “dead cycle” situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.

Intelligent Navigation Algorithm for Mobile Robots based on Optimized Fuzzy Logic

Ran Zhao(조연),Hong-Kyu Lee(이홍규) 한국전기전자학회 2018 전기전자학회논문지 Vol.22 No.2

본 논문은 미지 유동환경에서 다중 이동로봇들의 주행문제에 대한 연구결과이다. 여기에서 환경은 로봇에게는 알려져 있지 않기 때문에 로봇의 몸체에 부착된 근접센서들을 이용하여 주변환경들을 감지하여야 하고, 로봇이 충돌 없이 경로를 추적하여 목표지점에 도착하도록 기본 방책들을 조합한 지능주행 방법을 제안하였다. 이러한 대부분 기법들은 퍼지논리 제어기들을 이용하여 구현하였으며, 모든 로봇에 동일하게 적용하였다. 퍼지 제어기의 성능을 향상시키기 위해서 유전 알고리즘을 이용하여 퍼지 제어기의 membership function과 rules set를 진화시켰다. 모의실험 결과 제안한 방법이 주행문제에 긍정적인 결과가 있음이 증명되었다. The work presented in this paper deals with a navigation problem for a multiple mobile robots in unknown dynamic environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots’ bodies must be used to detect information about the surroundings. In order to guide the robots along collision-free paths to reach their goal positions, a navigation method based on a combination of primary strategies has been developed. Most of these strategies are achieved by means of fuzzy logic controllers, and are uniformly applied in every robot. In order to improve the performance of the proposed fuzzy logic, the genetic algorithms were used to evolve the membership functions and rules set of the fuzzy controller. The simulation experiments verified that the proposed method effectively addresses the navigation problem.

GA-Fuzzy based Navigation of Multiple Mobile Robots in Unknown Dynamic Environments

Ran Zhao(조연),Hong-Kyu Lee(이홍규) 대한전기학회 2017 전기학회논문지 Vol.66 No.2

The work present in this paper deals with a navigation problem for multiple mobile robots in unknown indoor environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots’ bodies must be used to detect information about the surroundings. The environments simulated in this work are dynamic ones which contain not only static but also moving obstacles. In order to guide the robot to move along a collision-free path and reach the goal, this paper presented a navigation method based on fuzzy approach. Then genetic algorithms were applied to optimize the membership functions and rules of the fuzzy controller. The simulation results verified that the proposed method effectively addresses the mobile robot navigation problem.

Sensor-based Navigation for Multiple Mobile Robots using Fuzzy Inference

Ran Zhao,DongHwan Lee,HongKyu Lee 한국지능시스템학회 2015 한국지능시스템학회 학술발표 논문집 Vol.25 No.2