Development of a ROS 2 Based Path Planning A* for Opponent Avoidance in Wheeled Soccer Robot
Abstract
The Indonesian Wheeled Soccer Robot Contest requires autonomous robots to navigate safely in dynamic environments where opponent robots continuously change their positions. Conventional Single A-star path planning generates the navigation path only once before robot movement, making it unable to adapt to obstacle movement during navigation. This study proposes a ROS 2-based Dynamic A-star path planning system for opponent avoidance in wheeled soccer robots. The proposed system performs real-time path replanning whenever the detected obstacle position changes, enabling the robot to generate an alternative collision-free trajectory. The system was evaluated in the Gazebo simulation environment using eight navigation scenarios and compared with the conventional Single A-star approach. The same robot starting positions and goal locations were used in both approaches, while the Dynamic A-star method extended the baseline configuration from one obstacle to two obstacles, including one moving obstacle. Experimental results showed that the proposed Dynamic A-star method achieved a 100% navigation success rate with a 0% collision rate, whereas the conventional Single A-star algorithm achieved a 0% navigation success rate with a 100% collision rate after obstacle movement. The average travel time increased from 19.50 s for Single A-star to 29.95 s for Dynamic A-star, while the average path length increased from 4.08 m to 6.76 m due to additional detours and path replanning. These results demonstrate that Dynamic A-star improves navigation adaptability and collision avoidance in dynamic environments. In addition, the ROS 2 framework provided real-time communication among perception, path planning, and robot control modules, supporting adaptive autonomous navigation for wheeled soccer robots.
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DOI: https://doi.org/10.21107/triac.v13i2.35303
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