00
Days
00
Hrs
00
Min
00
Sec
Submit Your Paper

Autonomous Litter Collecting Robot with Integrated Detection and Sorting Capabilities

Authors

Samkeliso Suku Dube

Department of Computer Science National University of Science and Technology, Bulawayo, Zimbabwe (ZW)

Mitchel Nothabo Magotsi

University of Science and Technology Bulawayo, Zimbabwe (ZW)

Tinahe Peswa Dube

Department of Agricultural Information Technology National University of Science and Technology Bulawayo, Zimbabwe (ZW)

Article Information

DOI: 10.51583/IJLTEMAS.2025.1408000011

Subject Category: Computer Science, machine learning, IoT

Volume/Issue: 14/8 | Page No: 79-85

Publication Timeline

Submitted: 2025-08-22

Published: 2025-08-22

Abstract

Abstract— This paper presents an autonomous robot that detects and collects litter in real time. The robot is designed for use in resource-limited urban environments in developing countries. Its main purpose is to automate the process of collecting waste and sorting it for recycling. It is made up of a combination of object detection using a raspberry pi camera module, autonomous navigation with ultrasonic sensors to measure the distance from obstacles, a YOLOv11 model to detect litter in real time and a custom robotic arm to collect the litter and sort it. Test results showed a detection accuracy of 87.87 %, with reliable navigation and collection performance. The system provides a practical and easy to scale solution for improving and supporting waste management in urban areas.

Keywords

YOLOv11, autonomous, litter, waste management, object detection, ultrasound sensors

Downloads

References

1. Achmad, F.I., Rosida, V.N., Kunto, A.W., Adi, K.S., Alfita, R., Sukri, H. and Rohman, G. (2021) ‘Waste Collector Roboboat Using Neural Network Method Based on Tensorflow Framework’, in E3S Web of Conferences. EDP Sciences. Available at: https://doi.org/10.1051/e3sconf/202132802003. [Google Scholar] [Crossref]

2. Ajibola, O. A., & Ogbolumani, O. A. (2024). Smart Battery Storage Integration in an IoT-Based Solar-Powered Waste Management System. Journal of Digital Food, Energy & Water Systems, 5(2). [Google Scholar] [Crossref]

3. Amato, C., Togo, C.A. (2021). Improper Municipal Solid Waste Disposal and the Environment in Urban Zimbabwe: A Case of Masvingo City, Ethiopian Journal of Environmental Studies and Management. [Google Scholar] [Crossref]

4. Bansal, S., Patel, S., Shah, I., Patel, .A. Makwana, Prof.J. and Thakker, Dr.R. (2019) ‘AGDC: Automatic Garbage Detection and Collection’. [Google Scholar] [Crossref]

5. Dube, S. S., Sanders, I., and Thomas, A. (2024). Detecting Informal Structures within a Formal Residential Area: A Case of Bulawayo Metropolitan Area. https://uir.unisa.ac.za/items/aeb3212a-3dc4-410d-a71b-70596535c0ea. [Google Scholar] [Crossref]

6. Koinig, G. (2023). Sensor-Based Sorting and Waste Management Analysis and Treatment of Plastic Waste with Special Consideration of Multilayer Films. [Google Scholar] [Crossref]

7. Kulshreshtha, M., Chandra, S.S., Randhawa, P., Tsaramirsis, G., Khadidos, A. and Khadidos, A.O. (2021) ‘Oatcr: Outdoor autonomous trash-collecting robot design using yolov4-tiny’, Electronics (Switzerland), 10(18). Available at: https://doi.org/10.3390/electronics10182292. [Google Scholar] [Crossref]

8. Liu, Ballatti and Kanoulas (no date) Garbage Collection and Sorting with a Mobile Manipulator using Deep Learning and Whole-Body Control, https://ieeexplore.ieee.org/abstract/document/9555800/authors#authors. [Google Scholar] [Crossref]

9. Malik, M., Prabha, C., Soni, P., Arya, V., Alhalabi, W.A., Gupta, B.B., Albeshri, A.A. and Almomani, A. (2023) ‘Machine Learning-Based Automatic Litter Detection and Classification Using Neural Networks in Smart Cities’, International Journal on Semantic Web and Information Systems, 19. Available at: https://doi.org/10.4018/IJSWIS.324105. [Google Scholar] [Crossref]

10. Mărgăritescu, M., Ancuța, P.N., Canale, E.V., Stanciu, D.I., Dumitriu, D. and Brișan, C.M. (2020) ‘Control of an Autonomous Mobile Waste Collection Robot’, in Lecture Notes in Networks and Systems. Springer, pp. 51–63. Available at: https://doi.org/10.1007/978-3-030-26991-3_6. [Google Scholar] [Crossref]

11. Milburn, L., Chiaramonte, J., Fenton, J., & Padir, T. (2023, December). TRASH: Tandem Rover and Aerial Scrap Harvester. In 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) (pp. 259-265). IEEE. [Google Scholar] [Crossref]

12. Mohan, M., Kuppan Chetty, R., Mohammed Azeem, K., Vishal, P., Poornasai, B. and Sriram, V. (2021) ‘Modelling and Simulation of Autonomous Indoor Robotic Wastebin in Webots for Waste Management in Smart Buildings’, IOP Conference Series: Materials Science and Engineering, 1012(1), p. 012022. Available at: https://doi.org/10.1088/1757-899x/1012/1/012022. [Google Scholar] [Crossref]

13. ] Mushiri, T. and Gocheki, E. (2019b) ‘Design of a Garbage Collection Robot’, in, pp. 90–169. Available at: https://doi.org/10.4018/978-1-5225-9924-1.ch004. [Google Scholar] [Crossref]

14. Rahman, M. M., Shahria, M. T., Sunny, M. S. H., Khan, M. M. R., Islam, E., Swapnil, A. A. Z., ... & Rahman, M. H. (2024). Development of a three-finger adaptive robotic gripper to assist activities of daily living. Designs, 8(2), 35. [Google Scholar] [Crossref]

15. Raj, J.R., Rajula, B.I.P., Tamilbharathi, R. and Srinivasulu, S. (2020) ‘AN IoT Based Waste Segreggator for Recycling Biodegradable and Non-Biodegradable Waste’, in 2020 6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020. Institute of Electrical and Electronics Engineers Inc., pp. 928–930. Available at: https://doi.org/10.1109/ICACCS48705.2020.9074251. [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles

© 2026 IJLTEMAS · RSIS International. All rights reserved. ISSN 2278-2540.