SF-TIM: 地形想像と計測を組み合わせた四足ロボットの跳躍敏捷性を高める簡易フレームワーク
SF-TIM: A Simple Framework for Enhancing Quadrupedal Robot Jumping Agility by Combining Terrain Imagination and Measurement
地形の想像と計測を統合した単一ポリシーで、四足ロボットの盲歩行能力を保ちつつ高所やギャップを跳び越える敏捷性を向上させ、実機でゼロショット転移を実現した。
著者: Ze Wang, Yang Li, Long Xu, Hao Shi, Zunwang Ma, Zhen Chu, Chao Li, Fei Gao, Kailun Yang, Kaiwei Wang
分類: cs.RO
原文アブストラクト
Dynamic jumping on high platforms and over gaps differentiates legged robots from wheeled counterparts. Dynamic locomotion on abrupt surfaces, as opposed to walking on rough terrains, demands the integration of proprioceptive and exteroceptive perception to enable explosive movements. In this paper, we propose SF-TIM (Simple Framework combining Terrain Imagination and Measurement), a single-policy method that enhances quadrupedal robot jumping agility, while preserving their fundamental blind walking capabilities. In addition, we introduce a terrain-guided reward design specifically to assist quadrupedal robots in high jumping, improving their performance in this task. To narrow the simulation-to-reality gap in quadrupedal robot learning, we introduce a stable and high-speed elevation map generation framework, enabling zero-shot simulation-to-reality transfer of locomotion ability. Our algorithm has been deployed and validated on both the small-/large-size quadrupedal robots, demonstrating its effectiveness in real-world applications: the robot has successfully traversed various high platforms and gaps, showing the robustness of our proposed approach. A demo video has been made available at https://flysoaryun.github.io/SF-TIM.
