In risky applications it is advantageous to use multiple robots in order to improve performances. In a research or patrol scenario robots have to move cooperatively in order to avoid collisions and to improve performance. In this paper we describe the implementation of two variations of a cooperative planning algorithm: Cooperative A* and Cooperative Voronoi A*. The task is decoupled into a ser...

Motion planning is a key element of robotics since it empowers a robot to navigate autonomously. Particle Swarm Optimization is a simple, yet a very powerful optimization technique which has been effectively used in many complex multi-dimensional optimization problems. This paper proposes a path planning algorithm based on particle swarm optimization for computing a shortest collision-free path...

Robot path-planning is one of the important issues in robotic navigation. This paper presents a novel robot path-planning approach based on the associative memory using Self-Organizing Incremental Neural Networks (SOINN). By the proposed method, an environment is first autonomously divided into a set of path-fragments by junctions. Each fragment is represented by a sequence of preliminarily gen...

This paper presents an improved genetic algorithm for mobile robot path planning. The algorithm uses artificial potential method to establish the initial population, and increases value weights in the fitness function, which increases the controllability of robot path length and path smoothness. In the new algorithm, a flip mutation operator is added, which ensures the individual population col...

Path planning contributes a very significant role in navigation of a mobile robot. The accuracy of path depends on mapping and localization of an indoor environment. A number of path planning approach are already in applications like A* Algorithms, D* Algorithm (Heuristic Approach), Dijkstra’s Algorithm (Deterministic approach), Cell Decomposition Technique etc. The conventional A* algorithm me...

The problem of path planning deals with the computation of an optimal path of the robot, from source to destination, such that it does not collide with any obstacle on its path. In this paper we solve the problem of path planning separately in two hierarchies. The coarser hierarchy finds the path in a static environment consisting of the entire robotic map. The resolution of the map is reduced ...

Because a robot usually operates in environments with uncertain information, path planning for the robot should be performed in real-time so as to match process speed based on sensors. This paper presents an efficient approach to behavior based motion planning of a manipulator with many degrees of freedom, which is based on an algorithm for fast mapping obstacles from a robot's workspace (W-spa...

To be competitive, an industrial robot picking fruits must be able to perform this task in an amount of time which compares to that needed by humans. Because the location of a fruit changes due to the picking of others, the determination of their location has to be performed on-line and also the associated path planning for the robot. This poses two major problems in the development of fruit-pi...

This paper presents a new way for mobile robots’ path planning which is based on the Evolutionary Artificial Potential Fields(EAPF) approach. The APF theory is a traditional method to plan path for a robot. The Evolutionary APF aims at helping a robot jump out of the local minimum point. Using a virtual goal to produce extra force and fixing the direction of the repulsive force are combined to ...

A shape-shifting robot with changeable configurations can accomplish search and rescue tasks which could not be achieved by manpower sometimes. The accessibility of this robot to uneven environment was efficiently enlarged by changing its configuration. In this paper, a path planning method is presented that integrates the reconfigurable ability of the robot with the potential field law. An ada...