Title: NAMOUnc: Navigation Among Movable Obstacles with Decision Making on Uncertainty Interval Show Chinese title

Title: NAMOUnc：具有不确定性区间决策的可移动障碍物导航

Abstract: Navigation among movable obstacles (NAMO) is a critical task in robotics, often challenged by real-world uncertainties such as observation noise, model approximations, action failures, and partial observability. Existing solutions frequently assume ideal conditions, leading to suboptimal or risky decisions. This paper introduces NAMOUnc, a novel framework designed to address these uncertainties by integrating them into the decision-making process. We first estimate them and compare the corresponding time cost intervals for removing and bypassing obstacles, optimizing both the success rate and time efficiency, ensuring safer and more efficient navigation. We validate our method through extensive simulations and real-world experiments, demonstrating significant improvements over existing NAMO frameworks. More details can be found in our website: https://kai-zhang-er.github.io/namo-uncertainty/ Show Chinese abstract

Abstract: 导航移动障碍物（NAMO）是机器人学中的关键任务，常常受到现实世界中的不确定性挑战，例如观测噪声、模型近似、动作失败和部分可观测性。 现有的解决方案通常假设理想条件，导致次优或有风险的决策。 本文介绍了NAMOUnc，一种新的框架，旨在通过将这些不确定性整合到决策过程中来解决这些问题。 我们首先估计它们，并比较移除和绕过障碍物的相应时间成本区间，优化成功率和时间效率，确保更安全和高效的导航。 我们通过大量模拟和真实实验验证了我们的方法，证明了相对于现有NAMO框架的显著改进。 更多细节请访问我们的网站：https://kai-zhang-er.github.io/namo-uncertainty/