外观
论文arXiv 2609.347021 个月前
MarsLab：用于行星车自主导航的火星车仿真器
原文链接：MarsLab: A Martian Rover Simulator for Planetary Rover Autonomous Navigation（arXiv 2609.34702 · 发布日期：2026-09-28）
MarsLab: A Martian Rover Simulator for Planetary Rover Autonomous Navigation
MarsLab面向火星车自主导航研究，基于ROS2与Isaac Sim构建可控火星环境，并在SLAM和VPR基准中验证。
核心要点
- 未来火星任务需在非结构地形、光照变化、尘埃和通信受限下自主运行。
- MarsLab是开源ROS2原生仿真器，结合HiRISE地形、程序化地形和可调场景因素。
- 在NVIDIA Isaac Sim中运行Perseverance级车模型，并通过ROS2发布多模态传感与GT位姿。
- SLAM和VPR基准展示了可控场景变化与共享GT轨迹用于比较估计和识别。
验证范围与局限：验证范围为仿真中的SLAM基准和重复Mars Base traversals上的VPR基准。
英文摘要 (Abstract)
Future Mars missions will require rover autonomy that can operate across unstructured terrain, changing illumination, atmospheric dust, and limited communication. Simulation is a practical way to study these conditions before deployment, but existing Mars-relevant resources differ in scope, including mission-oriented simulators, fixed analog datasets, task-specific environments, and open robotics interfaces. In this context, we present MarsLab, an open-source, ROS2-native Mars rover simulator for autonomy and navigation algorithm development. MarsLab combines HiRISE-derived and procedural terrain with customizable rock, crater, solar-illumination, and atmospheric-dust settings, and runs a Perseverance-class rover model in NVIDIA Isaac Sim. The runtime publishes RGB, depth, RGB-D point clouds, LiDAR, IMU, wheel odometry, and Ground Truth (GT) pose data through standard ROS2 topics. We demonstrate MarsLab with Simultaneous Localization and Mapping (SLAM) benchmarks across sensing modalities, dust levels, scene geometry, and route length, and with Visual Place Recognition (VPR) benchmarks over repeated Mars Base traversals under illumination and dust changes. The results illustrate how controlled scene variation and shared GT trajectories can be used to compare trajectory-level estimation and image-level place recognition within the same simulator. Our Project Page: https://kimhoyun-robotair.github.io/MarsLab/.
作者：Hoyun Kim, 김범수, Giseop Kim
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