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Applied Sciences
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Artificial Intelligence and Its Application in Robotics, 2nd Edition
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Artificial Intelligence and Its Application in Robotics, 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 July 2026 | Viewed by 881

Special Issue Editors

Dr. Seong Hyeon Hong

E-Mail Website
Guest Editor
Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA
Interests: intelligent perception and control; path planning; prognostics and health management; machine learning (physics-informed learning)
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yi Wang

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA
Interests: multidisciplinary analysis and optimization; large-scale system-level simulation; adaptive model integration; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Intelligent robots are critical in various domains such as personal service, medical support, smart manufacturing, transportation, military applications, smart farming, unmanned exploration, and various industrial applications. To facilitate and advance the technological developments in intelligent systems, the journal Applied Sciences invites you to propose novel research in the areas of artificial intelligence and robotics. This Special Issue seeks research dedicated to artificial intelligence applied across various fields of robotics, including but not limited to advanced perception (computer vision), intelligent control, reinforcement learning, meta-learning, human–robot interaction, human–machine interfaces, unmanned and autonomous systems, multi-robot systems, path planning, mapping, innovative sensor systems, field robotics, industrial robotics, medical robotics, and service robotics.

Dr. Seong Hyeon Hong
Prof. Dr. Yi Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • machine vision
  • robotic control systems
  • human–robot interaction
  • innovative sensors
  • unmanned vehicles
  • field/industrial robotics

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Published Papers (1 paper)

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Research

16 pages, 41514 KB  
Article
RBD-YOLOv10: A Lightweight Small-Object Detector for Laser-Tracking Cooperative Targets
by Dabao Lao, Tianqi Chen and Xiaojian Wang
Appl. Sci. 2026, 16(6), 2734; https://doi.org/10.3390/app16062734 - 12 Mar 2026
Viewed by 372
Abstract
Laser trackers (LTs) are essential instruments for large-scale equipment assembly and in situ measurement. However, their cooperative targets, Spherically Mounted Retroreflectors (SMRs), are often small, highly reflective, and prone to interference in complex industrial environments, making accurate detection difficult. Compared with generic small-object [...] Read more.
Laser trackers (LTs) are essential instruments for large-scale equipment assembly and in situ measurement. However, their cooperative targets, Spherically Mounted Retroreflectors (SMRs), are often small, highly reflective, and prone to interference in complex industrial environments, making accurate detection difficult. Compared with generic small-object detection, SMR detection during LT beam reacquisition is further challenged by specular highlights, halo-like blooming, and reflective background clutter, where SMRs may appear as minute bright spots with ambiguous boundaries. In this paper, we propose RBD-YOLOv10n, a lightweight detector tailored for SMRs based on the YOLOv10 framework. To improve robustness while keeping deployment efficient, we introduce three lightweight enhancements across the backbone, neck, and head, including RepNMSC, W-BiFPN, and DEHead. Validated on a custom SMR dataset, our method achieves an mAP@0.5 of 93.24% and an mAP@0.5:0.95 of 78.45%. Notably, the model is extremely lightweight, with 1.98M parameters and a 4.30 MB weight file (stored in FP16). These results show that the proposed method outperforms representative baseline detectors in balancing accuracy and efficiency, supporting practical high-precision LT vision-based SMR reacquisition under industrial conditions. Full article
(This article belongs to the Special Issue Artificial Intelligence and Its Application in Robotics, 2nd Edition)
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