AutoInspect：迈向长期自主工业检测
AutoInspect: Towards Long-Term Autonomous Industrial Inspection
AI总结：
AutoInspect通过基于ROS的系统实现长期自主工业检测，结合稳健映射与任务调度，在49天和35天的长期部署中展示了高效自主执行能力。
摘要：
我们概述了AutoInspect，一个基于ROS的软件系统，用于实现稳健且可扩展的任务级自主性。在过去的三年中，AutoInspect已在多种环境中部署，包括矿山、化工厂、模拟油 rigs、退役核电站和核聚变反应堆，持续时间从几小时到几周不等。该系统结合了稳健的映射和定位，基于图的自主导航、任务执行和调度，以实现完整的自主检测系统。从到达新地点到自主任务执行的时间可在一小时内完成。该系统部署在Boston Dynamics Spot机器人上，使用名为Frontier的定制传感和计算载具。在本文中，我们详细介绍了该系统在两个长期部署中的表现：在机器人测试设施中持续49天，以及在英国牛津郡的联合欧洲环形反应堆（JET）核聚变反应堆中持续35天。
英文摘要：
We give an overview of AutoInspect, a ROS-based software system for robust and extensible mission-level autonomy. Over the past three years AutoInspect has been deployed in a variety of environments, including at a mine, a chemical plant, a mock oil rig, decommissioned nuclear power plants, and a fusion reactor for durations ranging from hours to weeks. The system combines robust mapping and localisation with graph-based autonomous navigation, mission execution, and scheduling to achieve a complete autonomous inspection system. The time from arrival at a new site to autonomous mission execution can be under an hour. It is deployed on a Boston Dynamics Spot robot using a custom sensing and compute payload called Frontier. In this work we go into detail of the system's performance in two long-term deployments of 49 days at a robotics test facility, and 35 days at the Joint European Torus (JET) fusion reactor in Oxfordshire, UK.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
