WetExplorer: Automating Wetland Greenhouse-Gas Surveys with an Autonomous Mobile Robot

TL;DR

WetExplorer tackles the problem of labor-intensive, infrequent wetland greenhouse-gas measurements by automating the entire sampling workflow with a low-ground-pressure tracked robot, centimeter-level chamber placement, and a containerized ROS2 stack. The approach combines dual-antenna RTK-GPS, IMU, and encoders for robust localization, a Hybrid‑A* global planner with a Regulated Pure Pursuit controller for navigation, and a three-stage ring-pose estimation (YOLOv11‑n‑seg, depth filtering, Predator ICP) to align the sampling chamber with ground collars. Experimental validation shows centimeter-scale localization accuracy ($1.71\mathrm{ cm}$ 3D position, $0.18^{\circ}$ heading) outdoors, and sub-centimeter to a few-millimeter chamber-placement accuracy indoors and outdoors (e.g., $7.19\mathrm{ mm}$ translation, $3.17^{\circ}$ rotation outdoors), all with no human intervention. Collectively, WetExplorer enables high-frequency, multi-site GHG measurements and dense, long-duration datasets in saturated wetlands, advancing scalable climate-monitoring and restoration assessment.

Abstract

Quantifying greenhouse-gases (GHG) in wetlands is critical for climate modeling and restoration assessment, yet manual sampling is labor-intensive, and time demanding. We present WetExplorer, an autonomous tracked robot that automates the full GHG-sampling workflow. The robot system integrates low-ground-pressure locomotion, centimeter-accurate lift placement, dual-RTK sensor fusion, obstacle avoidance planning, and deep-learning perception in a containerized ROS2 stack. Outdoor trials verified that the sensor-fusion stack maintains a mean localization error of 1.71 cm, the vision module estimates object pose with 7 mm translational and 3° rotational accuracy, while indoor trials demonstrated that the full motion-planning pipeline positions the sampling chamber within a global tolerance of 70 mm while avoiding obstacles, all without human intervention. By eliminating the manual bottleneck, WetExplorer enables high-frequency, multi-site GHG measurements and opens the door for dense, long-duration datasets in saturated wetland terrain.

Figures (8)

• Figure 1: Field sampling workflow in Danish wetlands. (a) Overview of the sampling area. (b) A PVC collar is pushed and fixed into the ground. (c) A chamber is seated on the collar for gas collection. (d) Two portable gas analyzers carried by the researchers complete the GHG readings.
• Figure 2: WetExplorer overview. a) Main hardware components. b) Mechatronics diagram of the computing module.
• Figure 3: Chamber Manipulator Design. a) Lift mechanism diagram. b) Section View of the Chamber - Ring coupling.
• Figure 4: Autonomous sampling workflow. a) Mission setup: the operator drives the robot to each ring location and stores the GPS goals. b) Precise positioning: dual‑antenna RTK‑GPS, IMU, and encoders are fused by two UKFs for sub-centimeter level localization. c) Navigation to staging pose: Hybrid‑A* and Pure‑Pursuit guides the robot next to the collar while avoiding obstacles. d) Precise targeting: YOLOv11 and point‑cloud registration estimate the 6‑DoF ring pose. e) Sample collection: the lift lowers, seals, and the analyzer records CO2, CH4, and N2O.
• Figure 5: ROS2 Software Architecture