A novel autonomous microplastics surveying robot for beach environments

2025-08-04

AI Summary

Monitoring microplastic pollution on beaches is hindered by labor-intensive manual sampling, low operational efficiency, and the absence of in situ chemical characterization. Method: This study proposes a robotic system integrating vision-based and near-infrared (NIR) spectroscopic feedback to enable autonomous identification, precise localization, and compositional verification of microplastics. Leveraging a mobile robot platform, the system unifies deep learning–based camera-based instance segmentation, end-effector visual servoing, portable NIR sensing, and multimodal closed-loop control for end-to-end detection and analysis in complex sandy environments. Contribution/Results: Experimental validation demonstrates >92% classification accuracy and sub-millimeter localization precision in both laboratory and real-world beach settings. The system significantly enhances the automation level and reliability of in situ microplastic monitoring, establishing a deployable technical paradigm for dynamic environmental microplastic assessment.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Computer Vision: Vision for Robotics & Autonomous Driving
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

Abstract

Microplastics, defined as plastic particles smaller than 5 millimeters, have become a pervasive environmental contaminant that accumulates on beaches due to wind patterns and tidal forcing. Detecting microplastics and mapping their concentration in the wild remains one of the primary challenges in addressing this environmental issue. This paper introduces a novel robotic platform that automatically detects and chemically analyzes microplastics on beach surfaces. This mobile manipulator system scans areas for microplastics using a camera mounted on the robotic arm's end effector. The system effectively segments candidate microplastic particles on sand surfaces even in the presence of organic matter such as leaves and clams. Once a candidate microplastic particle is detected, the system steers a near-infrared (NIR) spectroscopic sensor onto the particle using both NIR and visual feedback to chemically analyze it in real-time. Through experiments in lab and beach environments, the system is shown to achieve an excellent positional precision in manipulation control and high microplastic classification accuracy.

Problem

• Detecting microplastics on beaches autonomously
• Mapping microplastic concentration in natural environments
• Chemically analyzing microplastics in real-time

Innovation

• Autonomous robot detects microplastics on beaches
• Uses NIR spectroscopy for real-time chemical analysis
• Combines visual and NIR feedback for high accuracy