Autonomous locomotion for mobile ground robots in unstructured environments such as waypoint navigation or flipper control requires a sufficiently accurate prediction of the robot-terrain interaction. Heuristics like occupancy grids or traversability maps are widely used but limit actions available to robots with active flippers as joint positions are not taken into account. We present a novel iterative geometric method to predict the 3D pose of mobile ground robots with active flippers on uneven ground with high accuracy and online planning capabilities. This is achieved by utilizing the ability of signed distance fields to represent surfaces with sub-voxel accuracy. The effectiveness of the presented approach is demonstrated on two different tracked robots in simulation and on a real platform. Compared to a tracking system as ground truth, our method predicts the robot position and orientation with an average accuracy of 3.11 cm and 3.91{\deg}, outperforming a recent heightmap-based approach. The implementation is made available as an open-source ROS package.

翻译：摘要：在非结构化环境中，移动地面机器人实现自主运动（如航点导航或履带控制）需要足够精确的机器人-地形交互预测。占位网格或可通行性地图等启发式方法被广泛使用，但由于未考虑关节位置，限制了具有主动履带的机器人可执行的动作。我们提出了一种新颖的迭代几何方法，用于在高精度和在线规划能力下预测主动履带移动地面机器人在不平坦地形上的3D位姿。该方法通过利用有符号距离场以亚体素精度表示表面的能力得以实现。通过两种不同履带机器人的仿真及真实平台实验展示了该方法的有效性。与作为真值的跟踪系统相比，我们的方法预测机器人位置和方向的平均精度分别为3.11 cm和3.91°，优于近期基于高度图的方法。该实现已作为开源ROS软件包发布。