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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Environmental Sources Human Health Effects Marine & Wildlife Policy & Risk Remediation Sign in to save

Beach Cleaning Robots a Comprehensive Survey of Technologies Challenges, and Future Directions

International Research Journal of Modernization in Engineering Technology and Science 2023 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Payas Deshpande, Omkar Milkhe, Ajinkya Kamble, Neha Kudu, M Browne, P Crump, S Niven, E Teuten, A Tonkin, T Galloway, T Siegler, M Perryman, A Andrady, . Law, K, C Erikson, R Mason, S Wilson, R Geyer, J Jambeck, K Law, P Randerson, C Di Giacomo, G Anfuso, A Macias, J Perales, S Gall, R Thompson, C Wilcox, E Van Sebille, B Hardesty, J Derraik, A Krelling, A Turra, B Gabrys, A Capra, A Corns, S Sankaran, Litterbot Team, V Subramanian, D Tudor, A Williams, S Yousefi, F Jazizadeh, R Moazenzadeh, M Karimi, M Gonza Lez-Rojas, J Guerrero-Iba N Ez, M Contreras-Cruz, R Romero-Troncoso, J Redmon, S Divvala, A Farhadi, W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, C Fu, A Berg, S Ren, K He, R Girshick, J Sun, A Gupta, A Sharma, P Tiwari

Summary

This paper is not relevant to microplastics; it is a survey of robotic technologies and methodologies for automated beach cleaning and litter removal.

Study Type Environmental

Beach pollution poses significant environmental, economic, and public health challenges worldwide. Traditional manual beach cleaning methods are labor-intensive, time-consuming, and often insufficient for thorough litter removal. As a result, there is a growing interest in automated beach cleaning solutions, particularly beach cleaning robots. This survey paper provides a comprehensive overview of the state-of-the-art in beach cleaning robot technology, examining key components, methodologies, and advancements in the field. We discuss the role of computer vision and object detection models in litter identification and classification, explore control systems and user interfaces for robot operation, and review power management and battery monitoring techniques. Furthermore, we identify the main challenges faced by beach cleaning robots and suggest potential improvements and research directions for addressing these issues. By highlighting the potential of beach cleaning robots in tackling beach pollution, this survey aims to encourage continued research and development in this critical area.

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