The Bulldozer Technique: Efficient Elimination of Local Minima Traps for APF-Based Robot Navigation

• URL: http://arxiv.org/abs/2512.23672v1
• Date: Mon, 29 Dec 2025 18:28:51 GMT
• Title: The Bulldozer Technique: Efficient Elimination of Local Minima Traps for APF-Based Robot Navigation
• Abstract summary: This paper proposes a novel path planning technique, termed the Bulldozer, which addresses the local minima problem.<n>The proposed technique is experimentally validated using a physical mobile robot across various maps with increasing complexity.<n>Results demonstrate that the Bulldozer technique effectively resolves the local minima problem while achieving superior execution speed and competitive path quality.
• Score: 2.612627266839037
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Path planning is a fundamental component in autonomous mobile robotics, enabling a robot to navigate from its current location to a desired goal while avoiding obstacles. Among the various techniques, Artificial Potential Field (APF) methods have gained popularity due to their simplicity, real-time responsiveness, and low computational requirements. However, a major limitation of conventional APF approaches is the local minima trap problem, where the robot becomes stuck in a position with no clear direction toward the goal. This paper proposes a novel path planning technique, termed the Bulldozer, which addresses the local minima issue while preserving the inherent advantages of APF. The Bulldozer technique introduces a backfilling mechanism that systematically identifies and eliminates local minima regions by increasing their potential values, analogous to a bulldozer filling potholes in a road. Additionally, a ramp-based enhancement is incorporated to assist the robot in escaping trap areas when starting within a local minimum. The proposed technique is experimentally validated using a physical mobile robot across various maps with increasing complexity. Comparative analyses are conducted against standard APF, adaptive APF, and well-established planning algorithms such as A*, PRM, and RRT. Results demonstrate that the Bulldozer technique effectively resolves the local minima problem while achieving superior execution speed and competitive path quality. Furthermore, a kinematic tracking controller is employed to assess the smoothness and traceability of the planned paths, confirming their suitability for real-world execution.

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