AutoInspect: Towards Long-Term Autonomous Industrial Inspection
arXiv:2404.12785 · doi:10.1109/TFR.2025.3586831
Abstract
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.
Accepted to the IEEE ICRA Workshop on Field Robotics 2024
References in corpus (8)
- The STRANDS Project: Long-Term Autonomy in Everyday Environments
- VILENS: Visual, Inertial, Lidar, and Leg Odometry for All-Terrain Legged Robots
- LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition
- Wildcat: Online Continuous-Time 3D Lidar-Inertial SLAM
- An Efficient Locally Reactive Controller for Safe Navigation in Visual Teach and Repeat Missions
- Flexible Supervised Autonomy for Exploration in Subterranean Environments
- Osprey: Multi-Session Autonomous Aerial Mapping with LiDAR-based SLAM and Next Best View Planning
- Watching Grass Grow: Long-term Visual Navigation and Mission Planning for Autonomous Biodiversity Monitoring