کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
413268 680387 2011 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Cellular ants: A method to create collision free trajectories for a cooperative robot team
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Cellular ants: A method to create collision free trajectories for a cooperative robot team
چکیده انگلیسی

Creating collision-free trajectories for mobile robots, known as the path planning problem, is considered to be one of the basic problems in robotics. In case of multiple robotic systems, the complexity of such systems increases proportionally with the number of robots, due to the fact that all robots must act as one unit to complete one composite task, such as retaining a specific formation. The proposed path planner employs a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques in order to create collision-free trajectories for every robot of a team while their formation is kept immutable. The method reacts with obstacle distribution changes and therefore can be used in dynamical or unknown environments, without the need of a priori knowledge of the space. The team is divided into subgroups and all the desired pathways are created with the combined use of a CA path planner and an ACO algorithm. In case of lack of pheromones, paths are created using the CA path planner. Compared to other methods, the proposed method can create accurate collision-free paths in real time with low complexity while the implemented system is completely autonomous. A simulation environment was created to test the effectiveness of the applied CA rules and ACO principles. Moreover, the proposed method was implemented in a system using a real world simulation environment, called Webots. The CA and ACO combined algorithm was applied to a team of multiple simulated robots without the interference of a central control. Simulation and experimental results indicate that accurate collision free paths could be created with low complexity, confirming the robustness of the method.

Research highlights
► Path planning in a cooperative robot team.
► Combination of Cellular Automata and Artificial Ant Colonies for collision free paths.
► Static and dynamic obstacle avoidance while retaining/regaining the team’s formation.
► Accurate real path creation with low complexity and no central interference.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Robotics and Autonomous Systems - Volume 59, Issue 2, February 2011, Pages 113–127
نویسندگان
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