An improved ant colony algorithm, differential evolution chaos ant colony optimization (DEACO) algorithm, was proposed to plan an optimal collision-free path for mobile robot in 3-D environment. It utilized differential evolution algorithm to update pheromone and chaos disturbance factor was added when pheromone updates for possible stagnation phenomenon. So it enhances escaping capability of algorithm, avoids path-deadlock situations as well as improves the efficiency of planning optimal path. The simulation results indicated that the optimal path on which the robot moves can reach safely and can be rapidly obtained under 3-D space environment, the effect being very satisfactory
This paper proposes an improved ant colony algorithm to achieve efficient searching capabilities of ...
This paper presents an efficient double-layer ant colony algorithm, called DL-ACO, for autonomous ro...
Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly ...
An improved ant colony algorithm, differential evolution chaos ant colony optimization (DEACO) algor...
ABSTRACT This paper presents an improved ant system algorithm for path planning of the mobile robo...
This paper uses the grid method with coding tactic based on effective vertexes of barriers (EVB-CT-G...
ABSTRACT This paper presents an improved ant system algorithm for path planning of the mobile robot...
The conventional ant colony algorithm is easy to fall into the local optimal in some complex environ...
The conventional ant colony algorithm is easy to fall into the local optimal in some complex environ...
Under the condition of known static environment and dynamic environment, an improved ant colony opti...
AbstractThe basic ant colony algorithm for mobile robot path planning exists many problems, such as ...
In order to solve the problems of deadlock, slow convergence, easy to get into local optimum and une...
To make robot avoid obstacles in 3D space, the Pheromone of Ant Colony Optimization(ACO)in Fuzzy Con...
The classical ant colony algorithm has the disadvantages of initial search blindness, slow convergen...
Ant colony algorithm suffers drawbacks such as slow convergence and easy to trap into local optimum,...
This paper proposes an improved ant colony algorithm to achieve efficient searching capabilities of ...
This paper presents an efficient double-layer ant colony algorithm, called DL-ACO, for autonomous ro...
Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly ...
An improved ant colony algorithm, differential evolution chaos ant colony optimization (DEACO) algor...
ABSTRACT This paper presents an improved ant system algorithm for path planning of the mobile robo...
This paper uses the grid method with coding tactic based on effective vertexes of barriers (EVB-CT-G...
ABSTRACT This paper presents an improved ant system algorithm for path planning of the mobile robot...
The conventional ant colony algorithm is easy to fall into the local optimal in some complex environ...
The conventional ant colony algorithm is easy to fall into the local optimal in some complex environ...
Under the condition of known static environment and dynamic environment, an improved ant colony opti...
AbstractThe basic ant colony algorithm for mobile robot path planning exists many problems, such as ...
In order to solve the problems of deadlock, slow convergence, easy to get into local optimum and une...
To make robot avoid obstacles in 3D space, the Pheromone of Ant Colony Optimization(ACO)in Fuzzy Con...
The classical ant colony algorithm has the disadvantages of initial search blindness, slow convergen...
Ant colony algorithm suffers drawbacks such as slow convergence and easy to trap into local optimum,...
This paper proposes an improved ant colony algorithm to achieve efficient searching capabilities of ...
This paper presents an efficient double-layer ant colony algorithm, called DL-ACO, for autonomous ro...
Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly ...