ALFRED mobile robot tracks plants over long periods outdoors
ALFRED: Requirement-driven development of an open-source mobile manipulator for long-term plant monitoring
RoboticsHardware ArchitectureComputer Vision and Pattern Recognition
Summary
Tracking crops and forests over seasons means checking the same plants again and again. The authors built ALFRED, a robot that can move around outside and use an arm with cameras and sensors to look at plants up close from many angles. They improved ALFRED through several versions to make it tough, easy to fix, and able to see more around it. ALFRED worked reliably for a year, monitoring forests monthly without missing a trip, even with battery wear and changes for different tasks. This shows how careful design helps robots keep working over long times in nature for plant studies.
What this means in practice
- •For field robotics teams: Use the ALFRED design and software to build robots that reliably monitor plants outdoors over many months with flexible sensing setups.
- •For forest monitoring groups: Deploy ALFRED for repeated, detailed observation of forest plots to track seasonal changes without missing scheduled data collections.
Authors
Ciarán Miceal Johnson, Christopher Quail, Garry Ellard, Alistair McConnell, Steve Tonneau, Fernando Auat Cheein
Abstract
Tracking seasonal change in crops and forests requires observing the same plants repeatedly. Ground robots can do this at close range, and a manipulator gives their sensors more viewpoints. Yet the robots behind long-term field datasets are rarely released with their design files, and how a robot's own structure limits arm reach and occludes its sensors is seldom compared between builds. We present ALFRED, an open-source mobile manipulator built from commercially available components. It carries a six-degree-of-freedom arm, LiDAR, RGB-D cameras, RTK GNSS and an IMU on an Ackermann-steered base, all mounted on a reconfigurable aluminium strut frame, and runs containerised ROS software. It was developed through four builds against six requirements for repeated outdoor deployment: durability, modularity, repairability, sensing reach, endurance and reproducibility. Model-based analysis of the last three builds shows the usable share of the arm's reachable poses rising from 34.0% to 60.0% and then 66.1%, and ray casting shows that only the final build keeps the frame-mounted LiDAR's horizontal view clear both forwards and backwards. ALFRED completed a year of monthly forest surveys (528 traversals) without missing a scheduled collection. This was despite battery degradation, reconfiguration for another researcher's study, and the parallel development of ALFRED 2.0 for autonomous crop-row operation, with each switch between builds taking about six hours. The deployment also showed that mechanical modularity is only as dependable as the robot description that tracks it.