Vector Field‐Based Collision‐Free Navigation in Tunnel‐Like Environments

ABSTRACT Tunnel‐like environments, renowned for their vast scale, confined spaces, and limited visibility, present significant challenges for autonomous robot navigation. This study addresses the critical issue of guiding robots through such environments while ensuring collision‐free navigation and maintaining a specified safety margin from both tunnel boundaries and internal obstacles. To achieve this, a novel navigation scheme is proposed, which leverages the principle of vector field (VF) to generate lightweight reactive responses. Environmental constraints, including tunnel boundaries and obstacles, are modeled using barrier functions. Specifically, the shapes of these obstacles are represented by zero‐level sets, which are approximated using smooth radial basis functions for precise and efficient modeling. The proposed method introduces a dual‐term VF design: The convergence term, derived from barrier functions associated with nearby boundaries, ensures adaptive adjustments to maintain a safe margin when the robot approaches boundaries. Meanwhile, the tangent term, constructed from the tangential vector of the tunnel‐like environment, guides the robot along the axial direction. Additionally, an adaptive obstacle avoidance mechanism dynamically generates obstacle‐based vectors and seamlessly interpolates them with the primary VF, ensuring smooth and collision‐free navigation. The proposed strategy has been validated through implementation and rigorous testing in both simulated and real‐world scenarios, demonstrating its effectiveness and reliability in navigating tunnel‐like environments.