Bipedal Navigation Planning over Rough Terrain using Traversability Models

被引:0
|
作者
McCrory, Stephen [1 ,2 ]
Mishra, Bhavyansh [1 ,2 ]
Griffin, Robert [1 ,2 ]
Pratt, Jerry [3 ]
Sevil, Hakki Erhan [2 ]
机构
[1] Inst Human & Machine Cognit IHMC, 40 S Alcaniz St, Pensacola, FL 32502 USA
[2] Univ West Florida UWF, 11000 Univ Pkwy, Pensacola, FL 32514 USA
[3] Figure AI Inc, Sunnyvale, CA USA
来源
关键词
VEHICLES;
D O I
10.1109/SoutheastCon51012.2023.10115107
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a planning framework designed for humanoid navigation over challenging terrain. This framework is designed to plan a traversable, smooth, and collision-free path using a 2.5D height map. The planner is comprised of two stages. The first stage consists of an A* planner which reasons about traversability using terrain features. A novel cost function is presented which encodes the bipedal gait directly into the graph structure, enabling natural paths that are robust to small gaps in traversability. The second stage is an optimization framework which smooths the path while further improving traversability. The planner is tested on a variety of terrains in simulation and is combined with a footstep planner and balance controller to create an integrated navigation framework, which is demonstrated on a DRC Boston Dynamics Atlas robot.
引用
收藏
页码:81 / 87
页数:7
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