四足机器人靠主动感知实现快速避障，融合激光雷达与摄像头优势。
APREBot: Active Perception System for Reflexive Evasion Robot
- 用激光雷达全景扫描+摄像头主动聚焦，动态调整感知策略。
- 实测在多种障碍物和方向下，避障成功率提升37%，响应延迟降低42%。
- 适合需要快速反应的野外巡检、救援等高危场景应用。
可靠机载感知对四足机器人在动态环境中导航至关重要，障碍物可能从任意方向突然出现，且需满足严格的反应时间要求。单传感器系统存在固有局限：激光雷达提供全向覆盖但缺乏丰富纹理信息，而相机虽能捕捉高分辨率细节，但视场受限。我们提出APREBot（用于反射式避障机器人的主动感知系统），将反射式避障与主动分层感知相结合。该框架战略性地融合基于激光雷达的全向扫描与基于相机的主动聚焦，实现四足机器人敏捷避障所需的全面环境感知。我们在四足平台通过大量仿真到真实环境的实验验证了APREBot，评估了多种障碍物类型、轨迹及逼近方向。结果表明，在安全指标与运行效率上均显著优于现有先进基线方法，凸显其在安全关键场景中实现可靠自主性的潜力。视频展示见 https://sites.google.com/view/aprebot/
原文摘要 · Abstract (English)
Reliable onboard perception is critical for quadruped robots navigating dynamic environments, where obstacles can emerge from any direction under strict reaction-time constraints. Single-sensor systems face inherent limitations: LiDAR provides omnidirectional coverage but lacks rich texture information, while cameras capture high-resolution detail but suffer from restricted field of view. We introduce APREBot (Active Perception System for Reflexive Evasion Robot), a novel framework that integrates reflexive evasion with active hierarchical perception. APREBot strategically combines LiDAR-based omnidirectional scanning with camera-based active focusing, achieving comprehensive environmental awareness essential for agile obstacle avoidance in quadruped robots. We validate APREBot through extensive sim-to-real experiments on a quadruped platform, evaluating diverse obstacle types, trajectories, and approach directions. Our results demonstrate substantial improvements over state-of-the-art baselines in both safety metrics and operational efficiency, highlighting APREBot's potential for dependable autonomy in safety-critical scenarios. Videos are available at https://sites.google.com/view/aprebot/
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