A new global path planning approach based on particle swarm optimization (PSO) for a mobile robot in a static environment is presented. Consider path planning as an optimization problem with constraints. The constraints are the path can not pass by the obstacles. The optimization target is the path is shortest. The obstacles in the robot’s environment are described as polygons and the vertexes ...

We propose an efficient and elegant heuristic algorithm for path planning that makes use of an elastic network. The network initializes as a simple straight path between the initial and goal positions. It then randomly samples the space around the areas of this initial path that lie inside obstacles, “pushing” the network away from the obstacles and thus determining an obstacle-free path. The f...

Optimal motion planning is critical for the successful operation of an autonomous mobile robot. Many proposed approaches use either fuzzy logic or genetic algorithms (GAs), however, most approaches offer only path planning or only trajectory planning, but not both. In addition, few approaches attempt to address the impact of varying terrain conditions on the optimal path. This paper presents a ...

A path planning method of mobile robot using both fuzzy logic and driver’s driving experience is proposed. Double layers fuzzy logic is used to control both the speed and the turning angle of the mobile robot. A method of “virtual target” is introduced to deal with the problem of local minimal, which often occurs in local path planning. The results of simulation and experiment show its effectiv...

The Robotic Remote Laboratory (RRL) controls the Robot labs via the Internet and applies the Robot experiment in easy and advanced way. If we want to enhance the RRL system, we must study requirements of the Robot experiment deeply. One of key requirements of the Robot experiment is the Control algorithm, which includes all important activities to affect the Robot; one of them relates the path ...

The paper describes a problem of multi-agent path planning in environment with obstacles. Novel approach to multi-agent optimal path planning, using graph representation of environment models is described. When planning the path of each robot, the graph model of environment is dynamically changed for path correction and collision avoidance. New algorithm applies changes of robots’ paths and spe...

Spherical mobile robot has good static and dynamic stability, which allows the robot to face different kinds of obstacles and moving surfaces, but the lack of effective control methods has hindered its application and development. In this paper, we propose a direct approach to path planning of a 2DOFs (Degrees of Freedom) spherical robot based on Bellman’s “Dynamic Programming” (DP). While othe...

Path planning is an essential component in the control software for an autonomous mobile robot. Evolutionary strategies are employed to determine optimal paths for their robustness and ability to solve complex problems. However, current evolutionary approaches fail to consider varying terrain conditions when determining an optimal path and offer only path planning without trajectory planning. T...

Path planning is the key task in the field of Robotics. The modelling environment and algorithm to find shortest, collision free path are the basic issues in the path planning problem of the robot motion planning. This paper presents a literature review of different path planning techniques in static as well as dynamic environment. Planning a path in static environment is easy as compared to dy...

The Bug algorithm is a local path planning methodology which detects the nearest obstacle as a mobile robot moves towards a target with limited information about the environment. It uses obstacle border as guidance toward the target. In Bug algorithm, the robot circumnavigates the obstacle till it finds certain condition to fulfill algorithm criteria to leave the obstacle toward target point. T...