ArticleSensors (Basel, Switzerland)2023
Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Sensor-Derived Mechanism-Informed Prediction of Section-Level Residual Profile Error in Robotic Blade-Edge Finishing.Sensors (Basel, Switzerland) · 2026Article
- An Adaptive Two-Dimensional Voxel Terrain Mapping Method for Structured Environment.Sensors (Basel, Switzerland) · 2023Article
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5 authors.
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Abstract
Legged robots can travel through complex scenes via dynamic foothold adaptation. However, it remains a challenging task to efficiently utilize the dynamics of robots in cluttered environments and to achieve efficient navigation. We present a novel hierarchical vision navigation system combining foothold adaptation policy with locomotion control of the quadruped robots. The high-level policy trains an end-to-end navigation policy, generating an optimal path to approach the target with obstacle avoidance. Meanwhile, the low-level policy trains the foothold adaptation network through auto-annotated supervised learning to adjust the locomotion controller and to provide more feasible foot placement. Extensive experiments in both simulation and the real world show that the system achieves efficient navigation against challenges in dynamic and cluttered environments without prior information.
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