不确定崎岖地形上的双足安全导航：统一地形建图与运动稳定性
Bipedal Safe Navigation over Uncertain Rough Terrain: Unifying Terrain Mapping and Locomotion Stability
AI总结：
针对不确定崎岖地形下双足机器人导航中地形建图与运动稳定性耦合的问题，提出分层感知运动动力学的采样导航规划器，结合GP地形学习与新轨迹评估指标，在Digit仿真中验证了有效性。
摘要：
我们研究双足机器人在存在不确定因素的崎岖地形等复杂环境中的导航问题。具体而言，我们考虑的场景是：机器人需要穿越地形高程不确定的环境，抵达期望的目标位置。这类地形不确定性不仅会产生无法通行的区域，还会引发机器人运动扰动。因此，地形建图与运动稳定性问题相互交织。我们评估了用于高斯过程（GP）回归的三种不同核函数，以学习地形高程。我们还学习了由地形，以及规划所用的降阶棱柱倒立摆模型（Prismatic Inverted Pendulum Model）与全阶运动动力学之间的差异共同导致的运动偏差。我们提出了一种分层的、感知运动动力学的基于采样的导航规划器。全局导航规划器在满足运动稳定性约束的前提下，规划一系列局部航点以抵达期望目标位置。随后，局部导航规划器生成一系列动力学可行的落脚点，以抵达局部航点。我们提出了一种新颖的轨迹评估指标，用于最小化运动偏差并最大化地形高程图的信息增益。我们在MuJoCo仿真环境中的Digit双足机器人上评估了该规划框架的有效性。
英文摘要：
We study the problem of bipedal robot navigation in complex environments with uncertain and rough terrain. In particular, we consider a scenario in which the robot is expected to reach a desired goal location by traversing an environment with uncertain terrain elevation. Such terrain uncertainties induce not only untraversable regions but also robot motion perturbations. Thus, the problems of terrain mapping and locomotion stability are intertwined. We evaluate three different kernels for Gaussian process (GP) regression to learn the terrain elevation. We also learn the motion deviation resulting from both the terrain as well as the discrepancy between the reduced-order Prismatic Inverted Pendulum Model used for planning and the full-order locomotion dynamics. We propose a hierarchical locomotion-dynamics-aware sampling-based navigation planner. The global navigation planner plans a series of local waypoints to reach the desired goal locations while respecting locomotion stability constraints. Then, a local navigation planner is used to generate a sequence of dynamically feasible footsteps to reach local waypoints. We develop a novel trajectory evaluation metric to minimize motion deviation and maximize information gain of the terrain elevation map. We evaluate the efficacy of our planning framework on Digit bipedal robot simulation in MuJoCo.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
