Robotic Sorting and Artificial Intelligence in Material Recovery Facilities: A Mixed-Methods Study of Published Research and Industry Perspectives

Published

October 30, 2026

Author(s)

Tanmay Haldankar, Kelsea Schumacher

Abstract

Material Recovery Facilities (MRFs) are essential to municipal recycling infrastructure, but face difficulties in sorting due to the growing complexity of recyclable material streams and contamination in their input. The limitations of traditional sorting technologies and reliance on manual sorters at MRFs has driven interest in integrating robotic systems that combine artificial intelligence (AI) detection with robotic actuation. This paper presents a review of AI and robotic sorting at MRFs, based on insights gained from reviewing recent literature as well as interviews with industry stakeholders. The literature review uncovered advances in AI algorithms and datasets, applications of new sensors and multi-modal sensing systems, and novel robotic gripping and grasping strategies. Industry discussions identified a shift toward deploying AI systems as standalone detection tools, particularly for quality control and facility monitoring, and a movement away from robotic integration due to limitations in speed, reliability, and gripper effectiveness. The analysis reveals three key challenge areas: (1) practical deployment and economic viability of robotic sorting systems, (2) limitations in AI performance and data availability, and (3) robot-specific challenges related to gripping and grasping. The paper outlines future research directions to address these challenges and advance the field.

Citation

Waste Management

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.wasman.2026.115830

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Keywords

Automation at Materials Recovery Facilities \sep AI sorting in Recycling \sep Robotic Waste Sorting \sep Robotic Integration Challenges

Citation

Haldankar, T. and Schumacher, K. (2026), Robotic Sorting and Artificial Intelligence in Material Recovery Facilities: A Mixed-Methods Study of Published Research and Industry Perspectives, Waste Management, [online], https://doi.org/10.1016/j.wasman.2026.115830, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=960572 (Accessed September 5, 2026)

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