外观
论文arXiv 2609.4008528 天前
BatSLAM 2.0：鲁棒位姿图中的序列验证声呐地点识别
原文链接：BatSLAM 2.0: Sequence-Verified Sonar Place Recognition in a Robust Pose Graph（arXiv 2609.40085 · 发布日期：2026-09-30）
BatSLAM 2.0: Sequence-Verified Sonar Place Recognition in a Robust Pose Graph
针对声呐地点识别歧义导致错误闭环和地图坍塌，BatSLAM 2.0结合声学前端、序列验证器与因子图位姿图，并在仿真和真实记录中验证。
核心要点
- 声呐地点识别天然存在歧义，走廊等场景会产生近似回波，错误闭环可能使拓扑地图坍塌。
- 系统仅使用声呐，由更新的声学前端、跟踪并验证闭环候选的序列验证器和高性能因子图位姿图组成。
- 在仿真和真实世界记录中充分评估，表现出鲁棒创建拓扑地图、抵抗地图坍塌和扩展地图规模的能力。
验证范围与局限：验证范围为仿真与真实世界记录，任务聚焦声呐地点识别和拓扑建图。
英文摘要 (Abstract)
Echolocating bats can navigate dark and cluttered spaces using echolocation. Over a decade ago, BatSLAM showed that a robot with a biomimetic binaural sonar can build a topological map of the environment, by recognizing places from the received acoustic signals. Sonar place recognition, however, is ambiguous by nature: corridors produce nearly identical echo trains, and wrong loop closure can collapse the topological map. In this paper, we introduce BatSLAM 2.0, a novel sonar-only SLAM system built from three elements: an updated acoustic front-end, a sequence verifier that tracks and verifies loop closure candidates and a pose graph implemented on a high performance factor graph framework. The system was thoroughly evaluated both in simulated as well as real world recordings. In both cases, the BatSLAM2.0 algorithm shows the capability of robust topological map creation, countering map collapse, and robust scaling of map size.
作者：Jan Steckel
来源
本页事实对应的公开页面，以原文为准。