When and where to step: Terrain-aware real-time footstep location and timing optimization for bipedal robots

计算机科学 地形 机器人 实时计算 人工智能 计算机视觉 模拟 嵌入式系统 人机交互 生态学 生物
作者
Ke Wang,Zhaoyang Jacopo Hu,Peter Tisnikar,Oskar Helander,Digby Chappell,Petar Kormushev
出处
期刊:Robotics and Autonomous Systems [Elsevier]
卷期号:179: 104742-104742
标识
DOI:10.1016/j.robot.2024.104742
摘要

Online footstep planning is essential for bipedal walking robots, allowing them to walk in the presence of disturbances and sensory noise. Most of the literature on the topic has focused on optimizing the footstep placement while keeping the step timing constant. In this work, we introduce a footstep planner capable of optimizing footstep placement and step time online. The proposed planner, consisting of an Interior Point Optimizer (IPOPT) and an optimizer based on Augmented Lagrangian (AL) method with analytical gradient descent, solves the full dynamics of the Linear Inverted Pendulum (LIP) model in real time to optimize for footstep location as well as step timing at the rate of 200 Hz. We show that such asynchronous real-time optimization with the AL method (ARTO-AL) provides the required robustness and speed for successful online footstep planning. Furthermore, ARTO-AL can be extended to plan footsteps in 3D, allowing terrain-aware footstep planning on uneven terrains. Compared to an algorithm with no footstep time adaptation, our proposed ARTO-AL demonstrates increased stability in simulated walking experiments as it can resist pushes on flat ground and on a 10° ramp up to 120 N and 100 N respectively. Videos2 and open-source code3 are released.
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