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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: closed (30 January 2026) | Viewed by 18833

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Prof. Dr. Yueh-Jaw (YJ) Lin

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Guest Editor

Mechanical Engineering Department, College of Engineering and Engineering Technology, Northern Illinois University, DeKalb, IL, USA
Interests: mechatronics engineering; applied robotics in design and automation; aircraft deicing and health monitoring; renewable energy and energy harvesting; global engineering education and research

Special Issue Information

Dear Colleagues,

Mechatronics and automation technologies significantly rely on the use of sensors, which play a pivotal role in collecting data, enabling precise control, ensuring the safety and efficiency of robotic systems, as well as enhancing the perception, navigation, and interaction capabilities of robots and mechatronic systems.

This Special Issue of Sensors titled ‘Applied Robotics in Mechatronics and Automation’ invites submissions of research articles that focus on the intersection of robotics, mechatronics and automation, highlight the recent advancements in their theoretical as well as practical applications, thereby underscoring the importance of applied robotics and automation technologies in the digital future.

Potential topics include, but are not limited to, robotics, mechatronics, automation, artificial intelligence, sensing technologies, human–machine interaction, industrial applications, autonomous systems, control systems, and machine learning.

Prof. Dr. Yueh-Jaw (YJ) Lin
Guest Editor

Manuscript Submission Information

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Published Papers (10 papers)

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Research

34 pages, 7792 KB

Open AccessArticle

Experimental Evaluation of UR5e Collaborative Robot Force Control in Low-Force Applications

by Roman Trochimczuk, Adam Wolniakowski, Michał Ostaszewski, Andrzej Burghardt and Piotr Borkowski

Sensors 2026, 26(5), 1709; https://doi.org/10.3390/s26051709 - 8 Mar 2026

Viewed by 487

Abstract

This article presents the findings of experimental research conducted to assess the stability of the force mode of the UR5e cobot from Universal Robots in the low-force range, from 1 N to 10 N. The set values of the robot’s forces and the physically measured values were verified by an OptoForce Hex six-axis Force/Torque sensor attached to the robot’s wrist, additionally coupled with an end-effector specially designed for research purposes. The results were recorded using proprietary software developed in the LabVIEW environment and a configured test lab station with a UR5e cobot. Three experimental tests were performed, in which the parameters of the effective force were measured while varying (1) the position of the task in the workspace of the robot, (2) the position and the level of force, and (3) the controller parameters of the force mode. The results of the experiments were compiled and presented in tables containing descriptions of, among other parameters, the following: the mean forces and their standard deviation; the mean maximum forces and its standard deviation; the mean root mean square error and its standard deviation; the mean absolute error and its standard deviation; the mean rate of force and its standard deviation; and the mean overshoot and its standard deviation. The findings of Experiment 1 demonstrated that when a setpoint of 10 N was employed, the UR5e cobot yielded an actual mean force ranging from 8.95 N to 13.26 N within the workspace plane. Experiment 2 showed that the average deviation from the set value within the 1–10 N range was approximately 0.38 N, with a maximum deviation of 0.61 N occurring at the limits of the working space. Experiment 3 showed that for the force range of 1–4 N, the best controller settings are Gain = 0.5 and Damping = 0.7; for the force range of 5–7 N: Gain = 1.0 and Damping = 0.6; and for the force range of 8–10 N: Gain = 2.0 and Damping = 0.8. Polynomial regression models were developed for each positioning scenario that can be used when making decisions regarding practical applications of the low-force mode. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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28 pages, 2684 KB

Open AccessArticle

Active Pitch Stabilization of Tracked Platforms Using a Nonlinear Dynamic Model for Coordinated Inertial Actuation

by Alina Fazylova, Kuanysh Alipbayev, Makpal Nogaibayeva, Teodor Iliev and Ivaylo Stoyanov

Sensors 2026, 26(5), 1517; https://doi.org/10.3390/s26051517 - 27 Feb 2026

Viewed by 459

Abstract

This study addresses the problem of actively stabilizing the longitudinal body inclination of a tracked mobile platform operating over uneven terrain. A novel drive system architecture is proposed that combines conventional track traction electric drives with an inertial body-stabilization drive based on a flywheel mounted on the pitch axis between the chassis and the body module. The main contribution of the proposed approach is the coordinated control of the traction drives and the inertial actuator based on a unified dynamic model of the platform. A quadratic performance criterion is formulated, and a coordinated optimal control law is synthesized to limit body angular oscillations while accounting for actuator energy consumption. Simulation results for motion over step-like and random terrain irregularities, as well as under external moment disturbances, demonstrate a significant reduction in both peak and root-mean-square pitch-angle deviations relative to configurations without an inertial actuator and with local body stabilization. The results obtained confirm the potential and effectiveness of inertial stabilization drives as part of coordinated drive control systems for tracked mobile platforms intended for special-purpose applications, and indicate prospects for their use in advanced terrestrial robotic platforms and future space robotic systems operating in challenging environments. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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24 pages, 28367 KB

Open AccessArticle

Hybrid Offline–Online Configuration Planning Approach for Continuum Robots Based on Real-Time Shape Estimation

by Hexiang Yuan, Zhibo Jing, Yibo He, Jianda Han and Juanjuan Zhang

Sensors 2026, 26(4), 1129; https://doi.org/10.3390/s26041129 - 10 Feb 2026

Viewed by 514

Abstract

Continuum robots possess highly flexible backbones, enabling remarkable adaptability and dexterity for motion in confined environments. However, this flexibility also introduces significant nonlinearities and uncertainties, making motion planning under physical constraints particularly challenging. To address this, a hybrid offline–online configuration planning framework is proposed in this work. Specifically, the configuration planning problem is formulated as a nonlinear optimization task that considers collision avoidance and structural constraints. A co-evolutionary strategy is incorporated into the differential evolution (DE) algorithm to decompose the target high-dimensional optimization problem. Then, an unscented Kalman filter (UKF)-based strategy is presented for real-time shape estimation using tip pose feedback for safe distance monitoring. Based on this shape feedback, an online configuration refiner is designed to locally adjust the preplanned configurations, thus leveraging the global perspective of the offline planning configuration to steer the continuum manipulator through constrained spaces. Validation and comparative experiments demonstrate the effectiveness of the proposed method, as well as its enhanced motion smoothness and safe motion performance in real-world environments. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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43 pages, 12726 KB

Open AccessArticle

Design, Analysis, and Prototyping of a Multifunctional Digital Twin-Enabled Aerospace Drilling End-Effector Deployable by a Collaborative Robot

by Mahdi Kazemiesfahani, Erfan Dilfanian, Bruno Monsarrat and Seyedhossein Hajzargarbashi

Sensors 2025, 25(24), 7504; https://doi.org/10.3390/s25247504 - 10 Dec 2025

Cited by 1 | Viewed by 1675

Abstract

Drilling in aerospace one-up assembly demands high positional accuracy, strong clamping forces, and precise angular compensation to ensure quality in multi-layered stacks. Existing robotic solutions achieve these requirements but are costly, bulky, and unsuitable for flexible or collaborative environments. This work introduces the Advanced Collaborative Multifunctional End-Effector (ACME), a lightweight robotic drilling end-effector designed for integration with collaborative robots (cobots). ACME incorporates vacuum-assisted clamping capable of generating high forces, a passive self-normalization mechanism for angular alignment on double-curvature surfaces, and a compact 5-DoF positioning system for precise positioning and orientation. The system’s kinematics and dynamics were modeled and experimentally verified through frequency response function (FRF) testing, enabling precise behavior prediction. The tool is integrated within a cyber–physical system (CPS) featuring an interactive digital twin that, unlike passive monitoring systems, allows operators to configure workpieces, select drilling locations directly from rendered CAD, and supervise execution without programming expertise. Experiments demonstrated average positional errors of 0.19 mm and normality deviations of 0.29°, both within aerospace standards. The results confirm that ACME effectively extends cobot capabilities for aerospace-grade drilling while improving flexibility, safety, and operator accessibility. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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21 pages, 9003 KB

Open AccessArticle

An Investigation on the Ball Screw-Based Variable Displacement Mechanism for Axial Piston Pumps with Feedforward Differential Input Control

by Guangcheng Zhang, Bokai Wang and Yueh-Jaw Lin

Sensors 2025, 25(4), 994; https://doi.org/10.3390/s25040994 - 7 Feb 2025

Cited by 2 | Viewed by 2061

Abstract

This paper proposes a variable mechanism structure based on a ball screw design for precise displacement control in axial piston pumps, with the objective of improving actuator position and velocity control within the displacement-controlled (DC) systems. Traditional valve-controlled cylinder variable mechanisms (VCCVM) often suffer from limited control precision over the swash plate due to numerous uncertain parameters within the hydraulic system. To address this issue, a ball screw is utilized to replace the original valve-controlled cylinder for swash plate control, enhancing accuracy and responsiveness. In addition, an in-depth analysis of the Ball Screw Variable Mechanism (BSVM) is conducted, leading to the development of a coupled mechanical–hydraulic dynamic model. Based on this model, a controller is designed to improve system performance. Finally, the effectiveness and high performance of the proposed new structure and control strategy were validated through comparative experiments and simulations. The experimental results confirm the advantages of the proposed design, demonstrating satisfactory improvements in control precision. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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18 pages, 1590 KB

Open AccessArticle

Design and Evaluation of a Low-Cost Mount for Attaching a Laser Tracker’s SMR to a Robot Flange

by Florian Stöckl, Silvan Müller, Marcus Strand and Markus Gardill

Sensors 2025, 25(1), 184; https://doi.org/10.3390/s25010184 - 31 Dec 2024

Cited by 1 | Viewed by 1874

Abstract

Robot calibration and modelling measurements are commonly performed using a laser tracker. To capture three-dimensional positions, a SMR is attached to the robot. While some researchers employ adhesive bonds for this purpose, such methods often result in inaccurate, unstable and non-repeatable SMR positioning, adversely affecting measurement precision and the traceability of research outcomes. To address these challenges, we investigated alternative methods for attaching an SMR to a robot’s flange to achieve both accuracy and repeatability. Additionally, we analysed measurement errors introduced when using a tool to attach the SMR to the flange. As a solution, we developed a 3D-printed mount designed for attachment to the flange. The mount’s accuracy was evaluated by assessing its eccentricity and the repeatability of the SMR placement. Experimental results demonstrated that the mount achieved an eccentricity radius of 0.35 mm and repeatability inaccuracies of

X = 0.075 mm

Y = 0.328 mm

, and

Z = 0.485 mm

. These values indicate that the mount provides sufficient accuracy to support calibration processes, ensures research traceability, and serves as a viable replacement for adhesive bonds. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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15 pages, 2177 KB

Open AccessArticle

DDNet: Depth Dominant Network for Semantic Segmentation of RGB-D Images

by Peizhi Rong

Sensors 2024, 24(21), 6914; https://doi.org/10.3390/s24216914 - 28 Oct 2024

Cited by 1 | Viewed by 3276

Abstract

Convolutional neural networks (CNNs) have been widely applied to parse indoor scenes and segment objects represented by color images. Nonetheless, the lack of geometric and context information is a problem for most RGB-based methods, with which depth features are only used as an auxiliary module in RGB-D semantic segmentation. In this study, a novel depth dominant network (DDNet) is proposed to fully utilize the rich context information in the depth map. The critical insight is that obvious geometric information from the depth image is more conducive to segmentation than RGB data. Compared with other methods, DDNet is a depth-based network with two branches of CNNs to extract color and depth features. As the core of the encoder network, the depth branch is given a larger fusion weight to extract geometric information, while semantic information and complementary geometric information are provided by the color branch for the depth feature maps. The effectiveness of our proposed depth-based architecture has been demonstrated by comprehensive experimental evaluations and ablation studies on challenging RGB-D semantic segmentation benchmarks, including NYUv2 and a subset of ScanNetv2. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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16 pages, 7405 KB

Open AccessArticle

Multi-AUV Kinematic Task Assignment Based on Self-Organizing Map Neural Network and Dubins Path Generator

by Xin Li, Wenyang Gan, Wen Pang and Daqi Zhu

Sensors 2024, 24(19), 6345; https://doi.org/10.3390/s24196345 - 30 Sep 2024

Cited by 4 | Viewed by 1790

Abstract

To deal with the task assignment problem of multi-AUV systems under kinematic constraints, which means steering capability constraints for underactuated AUVs or other vehicles likely, an improved task assignment algorithm is proposed combining the Dubins Path algorithm with improved SOM neural network algorithm. At first, the aimed tasks are assigned to the AUVs by the improved SOM neural network method based on workload balance and neighborhood function. When there exists kinematic constraints or obstacles which may cause failure of trajectory planning, task re-assignment will be implemented by changing the weights of SOM neurals, until the AUVs can have paths to reach all the targets. Then, the Dubins paths are generated in several limited cases. The AUV’s yaw angle is limited, which results in new assignments to the targets. Computation flow is designed so that the algorithm in MATLAB and Python can realize the path planning to multiple targets. Finally, simulation results prove that the proposed algorithm can effectively accomplish the task assignment task for a multi-AUV system. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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18 pages, 3329 KB

Open AccessArticle

Robot Calibration Sampling Data Optimization Method Based on Improved Robot Observability Metrics and Binary Simulated Annealing Algorithm

by Huakun Jia, Hanbo Zeng, Jiyan Zhang, Xiangyang Wang, Yang Lu and Liandong Yu

Sensors 2024, 24(19), 6171; https://doi.org/10.3390/s24196171 - 24 Sep 2024

Cited by 2 | Viewed by 2493

Abstract

As the societal demand for precision in industrial robot operations increases, calibration can enhance the end-effector positioning accuracy of robots. Sampling data optimization plays an important role in improving the calibration effect. In this study, a robot calibration sampling point optimization method based on improved robot observability metrics and a Binary Simulated Annealing Algorithm is proposed. Initially, a robot kinematic model based on the Product of Exponentials (POE) model and a generalized error model is established. By utilizing the least squares method, the ideal pose transformation relationship between the robot’s base coordinate system and the laser tracker measurement coordinate system is derived, resulting in an error calibration model based on spatial single points. An improved robot observability metric combined with the Binary Simulated Annealing Algorithm (BSAA) is introduced to optimize the selection of calibration sampling data. Finally, the robot’s parameter errors are obtained using a nonlinear least squares method. Experimental results demonstrate that the average end-effector positioning error of the robot after calibration can be reduced from 0.356 mm to 0.254 mm using this method. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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25 pages, 5922 KB

Open AccessArticle

GNSS-Based Narrow-Angle UV Camera Targeting: Case Study of a Low-Cost MAD Robot

by Ntmitrii Gyrichidi, Alexey M. Romanov, Oleg V. Trofimov, Stanislav A. Eroshenko, Pavel V. Matrenin and Alexandra I. Khalyasmaa

Sensors 2024, 24(11), 3494; https://doi.org/10.3390/s24113494 - 28 May 2024

Cited by 4 | Viewed by 2599

Abstract

One of the key challenges in Multi-Spectral Automatic Diagnostic (MAD) robot design is the precise targeting of narrow-angle cameras on a specific part of the equipment. The paper shows that a low-cost MAD robot, whose navigation system is based on open-source ArduRover firmware and a pair of low-cost Ublox F9P GNSS receivers, can inspect the 8 × 4 degree ultraviolet camera bounding the targeting error within 0.5 degrees. To achieve this result, we propose a new targeting procedure that can be implemented without any modifications in ArduRover firmware and outperforms more expensive solutions based on LiDAR SLAM and UWB. This paper will be interesting to the developers of robotic systems for power equipment inspection because it proposes a simple and effective solution for MAD robots’ camera targeting and provides the first quantitative analysis of the GNSS reception conditions during power equipment inspection. This analysis is based on the experimental results collected during the inspection of the overhead power transmission lines and equipment inspections on the open switchgear of different power plants. Moreover, it includes not only satellite, dilution of precision, and positioning/heading estimation accuracy but also the direct measurements of angular errors that could be achieved on operating power plants using GNSS-only camera targeting. Full article

(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)

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