两款球形机器人用于危险环境3D建图，发现高速运动导致定位漂移。
Design and Evaluation of Two Spherical Systems for Mobile 3D Mapping
- 用内外两种球形结构实现全向移动，搭载激光雷达与惯性算法
- 高速滚动使主流定位算法失效，导致全局地图不一致且漂移不可恢复
- 适合对移动稳定性有要求的工业巡检或灾害救援场景
球形机器人因其防护外壳和全向移动能力，在危险或狭小环境中具有独特优势。本文提出两种互补的球形建图系统：一种轻量化无驱动设计，另一种采用内部摆锤驱动的主动式变体。两者均配备Livox Mid-360固态激光雷达，并在资源受限硬件上运行激光雷达-惯性里程计（LIO）算法。通过将LIO生成的三维点云与真实地图对比，评估建图精度。结果表明，球形运动带来的高动态特性导致先进LIO算法性能下降，引发全局地图不一致及无法恢复的位姿漂移。
原文摘要 · Abstract (English)
Spherical robots offer unique advantages for mapping applications in hazardous or confined environments, thanks to their protective shells and omnidirectional mobility. This work presents two complementary spherical mapping systems: a lightweight, non-actuated design and an actuated variant featuring internal pendulum-driven locomotion. Both systems are equipped with a Livox Mid-360 solid-state LiDAR sensor and run LiDAR-Inertial Odometry (LIO) algorithms on resource-constrained hardware. We assess the mapping accuracy of these systems by comparing the resulting 3D point-clouds from the LIO algorithms to a ground truth map. The results indicate that the performance of state-of-the-art LIO algorithms deteriorates due to the high dynamic movement introduced by the spherical locomotion, leading to globally inconsistent maps and sometimes unrecoverable drift.
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