Construction of Potential Fields for the Local Navigation of Mobile Robots

2019 ◽  
Vol 55 (4) ◽  
pp. 371-375 ◽  
Author(s):  
A. B. Filimonov ◽  
N. B. Filimonov ◽  
A. A. Barashkov
Keyword(s):  
Mobile Robots ◽  
Potential Fields ◽  
Local Navigation

Issues of Motion Control of Mobile Robots Based on the Potential Guidance Method

2019 ◽  
Vol 20 (11) ◽  
pp. 677-685
Author(s):  
A. B. Filimonov ◽  
N. B. Filimonov
Keyword(s):  
Mobile Robots ◽  
Motion Control ◽  
A Priori ◽  
Target Position ◽  
Potential Fields ◽  
Modified Method ◽  
Working Space ◽  
Local Navigation ◽  
Virtual Forces ◽  
Priori Information

One of the topical areas of research in modern robotics is the problem of local navigation of mobile robots (MR), which ensures the movement of the robot to the target with the bypass of obstacles in the process of movement. The navigation process includes the following steps: mapping the environment, localization of the robot and planning the route leading to the goal. Among the popular methods of local navigation of robots is the method of artificial potential fields (PF). The essence of the PF method is to implement the movement of the MR in the field of "information forces" using the forces of "attraction" to the target position and the forces of "repulsion" from obstacles.This article addresses the issues of local navigation and motion control of the MR based on the method of PF.When using traditional attracting potential forces, the structure of virtual forces near the obstacle depends on the distance of the MR from the target, and the robot movement will slow down at the end of the route, which will inevitably lead to an unjustified tightening of the total time of moving the robot to the target position. To eliminate this undesirable effect, the authors propose to use attracting potential fields of special type.The authors propose new methods of PF allowing to solve the key problems for the control of MR — "traps" (potential pits) and bypass obstacles: the method of two maps of potential fields and the method of "fairway" on the map of potential fields. The methods of "beetle" for solving the problem of bypass obstacles in the condition of the absence of a priori information about the working space of MR are discussed. A modified method of "beetle" having a number of advantages in comparison with classical methods is proposed. 

scholarly journals Control of mobile robot formations using A-star algorithm and artificial potential fields

2021 ◽  
Vol 12 (2) ◽  
pp. 57-67
Author(s):  
Nelson Luis Manuel ◽  
Nihat İnanç ◽  
Mustafa Yasin Erten
Keyword(s):  
Stability Analysis ◽  
Mobile Robots ◽  
Programming Language ◽  
Lyapunov Theory ◽  
Potential Fields ◽  
Least Cost Path ◽  
Artificial Potential Fields ◽  
Or Groups ◽  
Linearized Model ◽  
Matlab Programming

Formations or groups of robots become essential in cases where a single robot is insufficient to satisfy a given task. With an increasingly automated world, studies on various topics related to robotics have been carried out in both the industrial and academic arenas. In this paper, the control of the formation of differential mobile robots based on the leader-follower approach is presented. The leader's movement is based on the least cost path obtained by the A-star algorithm, thus ensuring a safe and shortest possible route for the leader. Follower robots track the leader's position in real time. Based on this information and the desired distance and angle values, the leader robot is followed. To ensure that the followers do not collide with each other and with the obstacles in the environment, a controller based on Artificial Potential Fields is designed. Stability analysis using Lyapunov theory is performed on the linearized model of the system. To verify the implemented technique, a simulator was designed using the MATLAB programming language. Seven experiments are conducted under different conditions to show the performance of the approach. The distance and orientation errors are less than 0.1 meters and 0.1 radians, respectively. Overall, mobile robots are able to reach the goal position, maintaining the desired formation, in finite time.

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