For mobile robots, navigating cluttered or dynamic environments often necessitates non-prehensile manipulation, particularly when faced with objects that are too large, irregular, or fragile to grasp. The unpredictable behavior and varying physical properties of these objects significantly complicate manipulation tasks. To address this challenge, this manuscript proposes a novel Reactive Pushing Strategy. This strategy allows a mobile robot to dynamically adjust its base movements in real-time to achieve successful pushing maneuvers towards a target location. Notably, our strategy adapts the robot motion based on changes in contact location obtained through the tactile sensor covering the base, avoiding dependence on object-related assumptions and its modeled behavior. The effectiveness of the Reactive Pushing Strategy was initially evaluated in the simulation environment, where it significantly outperformed the compared baseline approaches. Following this, we validated the proposed strategy through real-world experiments, demonstrating the robot capability to push objects to the target points located in the entire vicinity of the robot. In both simulation and real-world experiments, the object-specific properties (shape, mass, friction, inertia) were altered along with the changes in target locations to assess the robustness of the proposed method comprehensively.

翻译：对于移动机器人而言，在杂乱或动态环境中导航时，往往需要采用非抓取式操作，尤其当遇到体积过大、形状不规则或易碎而难以抓取的物体时。这些物体不可预测的行为和变化的物理特性显著增加了操作任务的复杂性。为应对这一挑战，本文提出了一种新颖的反应式推搡策略。该策略允许移动机器人实时动态调整其基座运动，从而实现将物体成功推至目标位置的操作。值得注意的是，我们的策略基于覆盖基座的触觉传感器获得的接触位置变化来调整机器人运动，避免了对物体相关假设及其行为模型的依赖。该反应式推搡策略的有效性在仿真环境中进行了初步评估，其性能显著优于对比的基线方法。随后，我们通过真实世界实验验证了所提策略，展示了机器人将物体推至其周围任意目标点的能力。在仿真和真实实验中，我们均改变了物体的特定属性（形状、质量、摩擦力、惯性）以及目标位置，以全面评估所提方法的鲁棒性。