[
    {
        "id": "osp-18400",
        "type": "article-journal",
        "title": "Nudge Before You Push: Physics-Aware Navigation via Tactile Probing",
        "author": [
            {
                "family": "Li",
                "given": "Xianyao"
            },
            {
                "family": "Xu",
                "given": "Fang"
            },
            {
                "family": "Tian",
                "given": "Ruitong"
            },
            {
                "family": "Sun",
                "given": "Bowen"
            },
            {
                "family": "Hu",
                "given": "Xiao"
            },
            {
                "family": "Ye",
                "given": "Yang"
            },
            {
                "family": "Du",
                "given": "Jing"
            }
        ],
        "URL": "https://omanscience.com/ar/articles/nudge-before-you-push-physics-aware-navigation-via-tactile-probing",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Visually identical containers can conceal loads that require different handling decisions. We present TANav, which uses a brief nudge to measure push resistance for navigation under a site-defined handling boundary. TacPhys reads the force sequence, with optional RGB-D and kinematics, into a mass estimate for push authorization. A repeated-patrol planner weighs probe and route costs, requests a second contact when useful, and reuses observations across visits. In simulation, TacPhys approaches a resistance-only Bayes reference and reduces missed pushes from 28.7% to 5.5% relative to peak-force thresholding at comparable low-risk operating points. In repeated-patrol simulation, TANav recovers 90% of the oracle's path saving, more than halves human interventions relative to always-detour, and reduces boundary violations from 4.3% to 2.9% relative to RGB-D-only probing. On a quadruped manipulator with a Hall-array fingertip, offline zero-shot MAE is 0.28-1.07 kg on containers up to 2.82 kg. Force-rise calibration at 3 kg gives 93.5% pooled offline accuracy (86.4% on non-cube episodes); a separate raw-peak rule gives 15 of 20 correct online decisions on unseen boxes."
    }
]