Abstract:This paper deals with the navigation of a mobile robot in an unknown environment by using artificial potential field (APF) method. The aim is to develop a method for path planning of mobile robot from start point to the goal point while avoiding obstacles on robot's path. Artificial potential field method will be modified and optimized by using particle swarm optimization (PSO) algorithm to solve the drawbacks such as local minima and improve the quality of the trajectory of mobile robot.
“…When performing this attraction and repulsion task, environmental information is compared to a virtual force. Computations lead to loss of important information regarding the obstacles and cause local minima problem [36,40,41,105,106]. APF can also result in unstable state of the robot where the robot finds itself in a very small space [107].…”
Section: Challenges Of Conventional Path Planning Methodsmentioning
confidence: 99%
“…One of the popular methods used by researchers over the years is APF. APF is a mathematical method which causes a robot to be attracted to the goal but repelled by obstacles in the environment [6,34,36,37]. There are notable research works carried out using APF with sensors to plan the path of mobile robots to provide autonomous navigation, taking obstacle avoidance into consideration [12,[37][38][39][40][41][42][43][44][45][46][47].…”
Section: Artificial Potential Field Pathmentioning
Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.
“…When performing this attraction and repulsion task, environmental information is compared to a virtual force. Computations lead to loss of important information regarding the obstacles and cause local minima problem [36,40,41,105,106]. APF can also result in unstable state of the robot where the robot finds itself in a very small space [107].…”
Section: Challenges Of Conventional Path Planning Methodsmentioning
confidence: 99%
“…One of the popular methods used by researchers over the years is APF. APF is a mathematical method which causes a robot to be attracted to the goal but repelled by obstacles in the environment [6,34,36,37]. There are notable research works carried out using APF with sensors to plan the path of mobile robots to provide autonomous navigation, taking obstacle avoidance into consideration [12,[37][38][39][40][41][42][43][44][45][46][47].…”
Section: Artificial Potential Field Pathmentioning
Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.
“…Optimization of FOPID controllers needs to know the optimization goal, and then encode the parameters to be searched. [18,19]. The decoding values of the best chromosome are the optimized parameters of the FOPID controller.…”
This paper present a new control method for path tracking of mobile robot based on using fuzzy logic and FOPID controller . Two FOPID controllers are used. Parameters of the two FOPID controllers are optimized offline using genetic algorithm.. These optimized FOPID controllers are used for speed control and azimuth control. Parameters of these controller are adjusted online via fuzzy system. Each FOPID controller is supported by a fuzzy controller for adjusting the parameters online. The adjusting mechanism in the designed control scheme work well when there are variations in the plant parameters and changes in operating conditions.
“…Fuzzy logic controllers have been used in many applications . In the control systems, fuzzy logic is considered in the control of linear, nonlinear and complex nonlinear plants such as robotics power plants and induction motors [14,15,16,17 ]. Basics of a fuzzy model are explained in [18]:…”
This paper present an efficient robust design method of PID control scheme based on using fuzzy logic and particles swarm optimization (PSO) method for trajectory tracking of mobile robot. Two PID controllers are used. Parameters of PID controllers are optimized offline using PSO and fuzzy controller is used for tuning the parameters online . The two optimized PID controllers are used for speed control and azimuth control. The online fuzzy tuning in the designed control scheme work well when there are variations in the plant parameters and changes in operating conditions.
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