2025/09/29 by Zhipeng Xu, Xu, Zihao, Kuankuan Sima +9
Computer Science · #FOS: Computer and information sciences #Robotic Path Planning Algorithms #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2509.24733
openalex publication_date 2025/09/29 · openalex created_date 2025/10/19 · openalex updated_date 2026/07/28
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/