Abstract
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°, outperforming a recent heightmap-based approach. The implementation is made available as an open-source ROS package.
Abstract (translated)
自治移动地面机器人在非结构化环境中（如路径规划或翻转控制）实现自主移动需要对机器人与地面之间的相互作用进行足够准确的预测。类似于占用网格或可穿越性地图等启发式方法被广泛使用，但它们限制了具有活动翻板的机器人的可用动作，因为它们没有考虑到关节位置。我们提出了一种新颖的迭代几何方法，可以预测带有活动翻板的移动地面机器人在不平滑地面上的3D姿态，具有高精度和在线规划能力。这是通过利用签名距离场表示具有子像素准确度的表面来实现的。所提出的方法的有效性在模拟中和真实平台上进行了演示。与跟踪系统作为地面真实情况相比，我们的方法预测机器人的位置和方向具有平均准确度为3.11cm和3.91°，超过了最近基于高图的方法的性能。该实现可作为开源ROS包提供。
URL
https://arxiv.org/abs/2405.02121
