Document Type : Dynamics, Vibrations, and Control
Authors
1
Master's student, Iran University of Science and Technology, Tehran, Iran
2
Master's degree, Iran University of Science and Technology, Tehran, Iran
3
PhD, Iran University of Science and Technology, Tehran, Iran
4
Associate Professor, Iran University of Science and Technology, Tehran, Iran
Abstract
This study introduces a novel geometric algorithm for online path planning of autonomous robots in two-dimensional environments with convex obstacles. The proposed method models obstacles using optimized inscribed ellipses and generates candidate trajectories through tangent lines. By doing so, the planning problem at each step is confined to a convex region, and the optimal path is determined by minimizing a three-term cost function that incorporates path length, angular deviation, and obstacle clearance. This formulation not only simplifies the computational process but also supports rapid, real-time path updates in dynamic environments.
Extensive simulations confirm that the algorithm considerably outperforms well-established approaches such as A*, RRT*, and ACO. In the first test environment, it achieved an execution time of only 0.032 s (versus 3.981 s for A* and 4.1 s for RRT*), a path length of 1896.9 m (shorter than 1952.2 m for RRT*), and a smoothness value of 0.225 (compared with 696.6 for A* and 5.147 for RRT*). In the second environment, the computation time was 0.124 s and the smoothness 0.40, representing at least a 60% improvement over A* and a 20% improvement over RRT*. Furthermore, the method reduced the average energy consumption by 5–10% compared with competing algorithms.
Overall, the findings demonstrate that the proposed algorithm produces shorter, smoother, and more energy-efficient paths while significantly reducing computational cost. These advantages make it a promising candidate for large-scale, real-time robotic applications, with potential for further extension to three-dimensional environments.
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