停止并决策：用于无地图四足机器人巡检的延迟感知本体导航原语
Stop to Decide: Latency-Aware Proprioceptive Navigation Primitives for Mapping-Free Quadruped Inspection
浏览论文内容
中文总结 AI 辅助
研究计算能力受限的四足机器人导航延迟问题，提出基于逻辑剂量 - 反应模型的方法，探测器位于机载无地图无学习堆栈中，能在多种任务中良好表现，完成巡检路线，给出了如临界循环速率等部署规则。
中文摘要 AI 辅助
计算能力受限的四足机器人通常以远低于控制器设计速率运行其导航循环。例如，与视觉管道共享机载Jetson Orin会使楼梯循环减慢至约15Hz，这种延迟打破了标准本体感知模式。在一个顶部为50cm（短于机器人）的阶梯平台上，运动中检测会超出台阶顶部边缘，而攀爬 - 稳定节奏能在每个循环速率下将超调量保持在接近零。逻辑剂量 - 反应模型捕捉了失败情况，给出了部署规则。探测器位于完全机载、无地图且无学习的堆栈中，在55cm走廊中进行90度转弯等任务表现良好，18/20次试验（90%）完成巡检路线。结果来自单一课程几何、平台和操作员。
英文摘要
Onboard quadruped inspection systems often share limited compute between perception and navigation, reducing the rate at which event-triggered controllers evaluate proprioceptive signals. We study this latency in stair-summit detection and propose a climb--settle ``stop-to-decide'' cadence for structured, mapping-free inspection. On a Unitree Go2, the integrated stair loop ran at $\approx$15 Hz. On a three-level stepped platform whose 50 cm top was shorter than the robot, continuous-climb overshoot increased with per-period advance $v/f$, whereas the climb--settle cadence held observed overshoot near zero (22/45 vs 1/45 pooled over $\approx$30/20/15 Hz; Fisher $p\approx2.4\times10^{-7}$). A logistic dose--response model gives a model-based critical rate of $\approx$19 Hz at 0.30 m/s; a pre-specified 40 Hz held-out check was consistent with the protocol-clean fit. We integrated the detector with line following and a three-segment 90$^\circ$ corridor maneuver in a fully onboard, learning-free stack using an IMU, foot-force sensing, three 1-D ranges, and one line camera. The corridor maneuver completed 20/20 trials without contact, compared with 14/20 completions and 12 wall contacts for in-place yaw; the full course completed 18/20 trials. Results are limited to one calibrated course, robot, and operator but identify loop rate as a deployment parameter for proprioceptive event detection.
