New Trends in Robotics: Automation and Autonomous Systems

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Actuators actuators	2.3	4.3	2012	20.9 Days	CHF 2400	Submit
Automation automation	2.0	4.1	2020	30.9 Days	CHF 1200	Submit
Electronics electronics	2.6	6.1	2012	16.4 Days	CHF 2400	Submit
Eng eng	2.4	3.2	2020	18 Days	CHF 1400	Submit
Machines machines	2.5	4.7	2013	17.6 Days	CHF 2400	Submit
Robotics robotics	3.3	7.7	2012	23.7 Days	CHF 1800	Submit
Technologies technologies	3.6	8.5	2013	19.1 Days	CHF 1800	Submit

18 pages, 4762 KB

Open AccessArticle

Motion Planning and Control of Mobile Manipulators for Grasping-on-the-Move Tasks

by Zegang Sun, Shanlin Zuo, Qiang Jiang, Peng Zhang and Jiping Yu

Technologies 2026, 14(4), 210; https://doi.org/10.3390/technologies14040210 - 2 Apr 2026

Viewed by 645

Currently, most mobile manipulators employ a “Stop-and-Grasp” strategy, where the base of the manipulator stops before the arm executes the grasp. However, achieving “Grasping-on-the-Move” actions—where the robot grasps a target while the base is in motion—remains a significant challenge due to the coupling [...] Read more.

Currently, most mobile manipulators employ a “Stop-and-Grasp” strategy, where the base of the manipulator stops before the arm executes the grasp. However, achieving “Grasping-on-the-Move” actions—where the robot grasps a target while the base is in motion—remains a significant challenge due to the coupling of base and arm dynamics. To address this, we propose a two-phase collaborative motion planning framework. In the first phase (long-range approach), we introduce a spatially constrained visual servoing (SC-VS) method. By establishing a dynamic safety corridor based on the chassis path, this method ensures robust target tracking and obstacle avoidance for the arm during base motion. In the second phase (close-range grasping), to seize the brief grasping opportunity, we propose a Constrained-Sampling RRT-Connect (CSR-RRT-Connect) algorithm. By restricting the sampling region based on target prediction, this algorithm significantly reduces planning time. Comparative experiments demonstrate that our method achieves a 92% success rate at a base speed of 0.3 m/s, significantly outperforming the 46% success rate of baseline methods, while exhibiting superior robustness against dynamic operational disturbances and perception noise. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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23 pages, 4483 KB

Open AccessArticle

High-Precision Force Tracking Under Uncertainty: A Fuzzy-Adaptive Sliding-Mode Impedance Control Approach

by Zengpeng Lu, Jiarui Li, Jianlei Fan and Xirui Fan

Technologies 2026, 14(4), 195; https://doi.org/10.3390/technologies14040195 - 24 Mar 2026

Viewed by 356

Abstract

Achieving high-precision force tracking in robotic physical interaction remains challenging in the presence of environmental and dynamic model uncertainties. Conventional impedance control strategies often exhibit excessive force overshoot at contact onset and persistent steady-state errors under uncertain or time-varying interaction conditions. To overcome [...] Read more.

Achieving high-precision force tracking in robotic physical interaction remains challenging in the presence of environmental and dynamic model uncertainties. Conventional impedance control strategies often exhibit excessive force overshoot at contact onset and persistent steady-state errors under uncertain or time-varying interaction conditions. To overcome these limitations, this paper proposes a fuzzy-adaptive sliding-mode impedance control approach. During the initial contact phase, a tracking differentiator (TD) is employed to generate a smooth and dynamically feasible force reference, effectively suppressing impulsive force transients without requiring explicit contact detection. Furthermore, a fuzzy-logic-modulated adaptive law is developed to adjust online the adaptation gains of the impedance controller, thereby asymptotically eliminating steady-state tracking errors while preserving Lyapunov stability. In addition, a composite PD–suboptimal sliding-mode control law is embedded within the impedance loop to enhance robustness against external disturbances while ensuring continuous, chattering-free control action. The proposed architecture requires no prior knowledge of environmental stiffness and is provably robust to model inaccuracies and unstructured disturbance. Simulation and experimental results conducted on a 6-DOF robotic manipulator demonstrate that, under realistic uncertain contact scenarios and in comparison with three benchmark methods, the proposed approach reduces overshoot by 26%, shortens settling time by 30%, and decreases steady-state error by 48%. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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21 pages, 7075 KB

Open AccessArticle

Robust Backstepping Control of a Twin Rotor MIMO System via an RBF-Tuned High-Gain Observer

by Azeddine Beloufa, Souaad Tahraoui, Abderrahmane Kacimi, Hadje Allouache, Jun-Jiat Tiang, Abdelbasset Azzouz and Mehdi Houari Zaid

Automation 2026, 7(2), 40; https://doi.org/10.3390/automation7020040 - 27 Feb 2026

Cited by 1 | Viewed by 475

Abstract

The design of robust controllers for complex nonlinear systems remains a formidable challenge, particularly concerning the disparity between simulation performance and real-world implementation constraints. This research investigates the practical implementation of a backstepping controller integrated with a High-Gain Observer (HGO) on a Twin [...] Read more.

The design of robust controllers for complex nonlinear systems remains a formidable challenge, particularly concerning the disparity between simulation performance and real-world implementation constraints. This research investigates the practical implementation of a backstepping controller integrated with a High-Gain Observer (HGO) on a Twin Rotor MIMO System (TRMS). While the control architecture exhibited stability and precise tracking in simulation, physical deployment initially failed due to sensitivity to measurement noise and the peaking phenomenon, resulting in a divergent response with a Yaw RMSE of 2.56 rad. Unlike conventional approaches that attempt to bridge the simulation-to-reality gap by optimizing the controller, we hypothesized that the critical bottleneck lay within the observer dynamics. To address this, a Radial Basis Function (RBF) Neural Network was employed to adaptively tune the observer gains in real time. Experimental results demonstrate that this adaptive mechanism successfully mitigated the effects of unmodeled dynamics and noise, reducing the Root Mean Square Error (RMSE) by over 85% in the pitch axis and 95% in the yaw axis. These findings substantiate that online adaptive observer tuning is a decisive strategy for ensuring the reliability of advanced nonlinear controllers on physical hardware. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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18 pages, 908 KB

Open AccessArticle

Event-Triggered Control Protocols for Achieving Bipartite Consensus in Switched Multi-Agent Systems

by Yijun Zhang, Zonglin Zou and Ku Du

Automation 2026, 7(1), 22; https://doi.org/10.3390/automation7010022 - 21 Jan 2026

Viewed by 548

Abstract

This paper investigates the bipartite consensus problem for multi-agent systems subject to both switching dynamics and external disturbances within an event-triggered control (ETC) framework. The investigation commences with an analysis of time-invariant systems to establish bipartite consensus, and subsequently expands the framework to [...] Read more.

This paper investigates the bipartite consensus problem for multi-agent systems subject to both switching dynamics and external disturbances within an event-triggered control (ETC) framework. The investigation commences with an analysis of time-invariant systems to establish bipartite consensus, and subsequently expands the framework to accommodate the complexities of switched systems. In time-invariant systems, agents update their states only when the event-triggering threshold is exceeded; the convergence of this mechanism can be rigorously established via an error dynamics mode. For switched systems, the system state is also updated solely when the event-triggering condition is met. Once all subsystems are stabilized, we design an appropriate mean sojourn time to mitigate state jumps caused by switching, thus ensuring bipartite consensus. Finally, four case studies based on numerical simulations to verify the theoretical results. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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20 pages, 1440 KB

Open AccessArticle

Robust Optimization and Workspace Enhancement of a Reconfigurable Delta Robot via a Singularity-Sensitive Index

by Arturo Franco-López, Mauro Maya, Alejandro González, Liliana Félix-Ávila, César-Fernando Méndez-Barrios and Antonio Cardenas

Robotics 2026, 15(1), 11; https://doi.org/10.3390/robotics15010011 - 30 Dec 2025

Viewed by 893

Abstract

This study investigates the kinematic behavior of a reconfigurable Delta parallel robot aiming to enhance its performance in real industrial applications such as high-speed packaging, precision pick-and-place operations, automated inspection, and lightweight assembly tasks. While Delta robots are widely recognized for their speed [...] Read more.

This study investigates the kinematic behavior of a reconfigurable Delta parallel robot aiming to enhance its performance in real industrial applications such as high-speed packaging, precision pick-and-place operations, automated inspection, and lightweight assembly tasks. While Delta robots are widely recognized for their speed and accuracy, their practical use is often limited by workspace constraints and singularities that compromise motion stability and control safety. Through a detailed analysis, it is shown that classical Jacobian-based performance indices are unsuitable for resolving the redundancy introduced by geometric reconfiguration, as they may lead the system toward singular or ill-conditioned configurations. To overcome these limitations, this work introduces an adjustable singularity-sensitive performance index designed to penalize extreme velocity and force singular values and enables tuning between velocity and force performance. Simulation results demonstrate that optimizing the reconfiguration parameter using this index increases the usable workspace by approximately 82% and improves the uniformity of manipulability across the workspace. These findings suggest that the proposed approach provides a robust framework for enhancing the operational range and kinematic safety of reconfigurable Delta robots, while remaining adaptable to different design priorities. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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18 pages, 3437 KB

Open AccessArticle

Development of an Autonomous Robot for Precision Floor Marking

by Fatimah Alahmed, Muhammad Hawwa and Uthman Baroudi

Robotics 2026, 15(1), 7; https://doi.org/10.3390/robotics15010007 - 29 Dec 2025

Viewed by 1499

Abstract

The construction and facilities management sectors are increasingly adopting automation technologies to improve productivity and reduce manual labor. In parallel, decorative and informational floor-marking is widely used in indoor environments such as schools, exhibition halls, and public spaces to support organization, wayfinding, and [...] Read more.

The construction and facilities management sectors are increasingly adopting automation technologies to improve productivity and reduce manual labor. In parallel, decorative and informational floor-marking is widely used in indoor environments such as schools, exhibition halls, and public spaces to support organization, wayfinding, and visual communication. While robotic systems have been developed for floor and layout marking, many existing solutions rely on specialized infrastructure or offer limited flexibility in the range of patterns that can be produced. This paper presents the development of a prototype of a mobile, wheeled robot capable of autonomously executing diverse designs on surfaces such as fields and floors. The robot’s potential applications include use on indoor floors and exhibition halls. It marks the ground using a plotting pen while navigating and avoiding obstacles within its environment. Additionally, the robot can produce a range of drawings, including letters and signage, and its capabilities can be extended to create decorative patterns as well as marks for floor-based games. This robot was constructed entirely from cost-effective, commercially available components. Experimental evaluation demonstrates repeatable motion and drawing performance, with measured standard deviations of approximately 1.6 mm in forward motion and 3 mm in lateral motion during representative grid-based traversal. These results indicate that the proposed approach achieves a level of accuracy and consistency sufficient for decorative floor-marking and similar applications, without reliance on external localization infrastructure. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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21 pages, 2648 KB

Open AccessArticle

A Hybrid Reinforcement Learning Framework Combining TD3 and PID Control for Robust Trajectory Tracking of a 5-DOF Robotic Arm

by Zied Ben Hazem, Firas Saidi, Nivine Guler and Ali Husain Altaif

Automation 2025, 6(4), 56; https://doi.org/10.3390/automation6040056 - 14 Oct 2025

Cited by 21 | Viewed by 3083

Abstract

This paper presents a hybrid reinforcement learning framework for trajectory tracking control of a 5-degree-of-freedom (DOF) Mitsubishi RV-2AJ robotic arm by integrating model-free deep reinforcement learning (DRL) algorithms with classical control strategies. A novel hybrid PID + TD3 agent is proposed, combining a [...] Read more.

This paper presents a hybrid reinforcement learning framework for trajectory tracking control of a 5-degree-of-freedom (DOF) Mitsubishi RV-2AJ robotic arm by integrating model-free deep reinforcement learning (DRL) algorithms with classical control strategies. A novel hybrid PID + TD3 agent is proposed, combining a Proportional–Integral–Derivative (PID) controller with the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, and is compared against standalone TD3 and PID controllers. In this architecture, the PID controller provides baseline stability and deterministic disturbance rejection, while the TD3 agent learns residual corrections to enhance tracking accuracy, robustness, and control smoothness. The robotic system is modeled in MATLAB/Simulink with Simscape Multibody, and the agents are trained using a reward function inspired by artificial potential fields, promoting energy-efficient and precise motion. Extensive simulations are performed under internal disturbances (e.g., joint friction variations, payload changes) and external disturbances (e.g., unexpected forces, environmental interactions). Results demonstrate that the hybrid PID + TD3 approach outperforms both standalone TD3 and PID controllers in convergence speed, tracking precision, and disturbance rejection. This study highlights the effectiveness of combining reinforcement learning with classical control for intelligent, robust, and resilient robotic manipulation in uncertain environments. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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40 pages, 10028 KB

Open AccessArticle

Collaborative Optimization Control of Gravity Center and Pose of Hexapod Robot in Complex Terrains

by Chenjiang Yu, Diqing Fan and Xintian Liu

Machines 2025, 13(9), 871; https://doi.org/10.3390/machines13090871 - 18 Sep 2025

Cited by 1 | Viewed by 1659

Abstract

The adaptability of a hexapod robot to complex terrain is highly dependent on its own posture, which directly affects its stability and flexibility. In order to adapt to a change in terrain, it is necessary to adjust posture in real time when walking. [...] Read more.

The adaptability of a hexapod robot to complex terrain is highly dependent on its own posture, which directly affects its stability and flexibility. In order to adapt to a change in terrain, it is necessary to adjust posture in real time when walking. At the same time, external factors such as ground state and landing impact will also interfere with posture. Therefore, it is necessary to maintain balance after adjustment. This paper proposes a pose adjustment method utilizing joint angle control. It enhances robot stability, flexibility, and terrain adaptability through torso posture and center of gravity optimization, aiming to maintain balance. The strategy’s effectiveness was validated via Adams–Simulink co-simulation. Optimal position and posture adjustment for the torso was then implemented at the six-legged support stage after each step, employing inverse kinematics and a triangular gait. It is found that without pose adjustment, the direction deviation will accumulate and significantly deviate from the trajectory. The introduction of this adjustment can effectively correct the direction deviation and torso posture angle, increase the stability margin, ensure stable straight-line walking, and significantly reduce joint energy consumption. Crawling experiments with the physical prototype further validate the strategy. It rapidly counters instantaneous attitude fluctuations during leg alternation, maintaining a high stability margin and improving locomotion efficiency. Consequently, the robot achieves enhanced directional stability, overall stability, and energy efficiency when traversing terrain. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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27 pages, 2922 KB

Open AccessArticle

Methodology for Modeling Coupled Rigid Multibody Systems Using Unitary Quaternions: The Case of Planar RRR and Spatial PRRS Parallel Robots

by Francisco Cuenca Jiménez, Eusebio Jiménez López, Mario Acosta Flores, F. Peñuñuri, Ricardo Javier Peón Escalante and Juan José Delfín Vázquez

Robotics 2025, 14(7), 94; https://doi.org/10.3390/robotics14070094 - 3 Jul 2025

Cited by 1 | Viewed by 1371

Abstract

Quaternions are used in various applications, especially in those where it is necessary to model and represent rotational movements, both in the plane and in space, such as in the modeling of the movements of robots and mechanisms. In this article, a methodology [...] Read more.

Quaternions are used in various applications, especially in those where it is necessary to model and represent rotational movements, both in the plane and in space, such as in the modeling of the movements of robots and mechanisms. In this article, a methodology to model the rigid rotations of coupled bodies by means of unit quaternions is presented. Two parallel robots were modeled: a planar RRR robot and a spatial motion PRRS robot using the proposed methodology. Inverse kinematic problems were formulated for both models. The planar RRR robot model generated a system of 21 nonlinear equations and 18 unknowns and a system of 36 nonlinear equations and 33 unknowns for the case of space robot PRRS; both systems of equations were of the polynomial algebraic type. The systems of equations were solved using the Broyden–Fletcher–Goldfarb–Shanno nonlinear programming algorithm and Mathematica V12 symbolic computation software. The modeling methodology and the algebra of unitary quaternions allowed the systematic study of the movements of both robots and the generation of mathematical models clearly and functionally. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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23 pages, 4415 KB

Open AccessArticle

Efficient and Effective Irrigation Water Management Using Sprinkler Robot

by Nabil Elkaoud, Saleh Ismail, Ragab Mahmoud, Hassan Taraby, Shuqi Shang, Dongwei Wang and Mostafa Rayan

Eng 2025, 6(7), 138; https://doi.org/10.3390/eng6070138 - 24 Jun 2025

Viewed by 3833

Abstract

This manuscript addresses the issue of irrigation water management with high efficiency and effectiveness and focuses on systems associated with significant water losses, which is sprinkler irrigation. This article presents mathematical modeling that enables the application of precision irrigation using a gun sprinkler [...] Read more.

This manuscript addresses the issue of irrigation water management with high efficiency and effectiveness and focuses on systems associated with significant water losses, which is sprinkler irrigation. This article presents mathematical modeling that enables the application of precision irrigation using a gun sprinkler robot. The sprinkler robot was fabricated in the Faculty of Agriculture and Natural Resources workshop at As-wan University. The experiments were conducted using 12, 14, and 16 mm nozzle sizes and three gun heights, 1.25, 1.5, and 2 m, at three forward speeds, 25, 50, and 75 m/h. The results revealed that at nozzle 12, the actual wetted diameter would be less than the theoretical diameter by a percentage of 2–5%, while at nozzle 14, it ranged from 2 to 7%, but at nozzle 16, it increased from 6 to 9%. The values of evaporation and wind drift losses were always less than 2.8 mm. The highest efficiency was achieved at the lowest forward speed (25 m/h) and using a 1.5 m gun height. The highest water application efficiency was 81.8, 82.5, and 81.1% using nozzle 12, nozzle 14, and nozzle 16, respectively. Precise irrigation control using sensor and variable rate technology will be the preferred option in the future. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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25 pages, 1931 KB

Open AccessArticle

Geometric Path Planning and Synchronization for Multiple Vehicles

by Hongjun Yu and Lanyong Zhang

Robotics 2025, 14(4), 47; https://doi.org/10.3390/robotics14040047 - 11 Apr 2025

Viewed by 1495

Abstract

In known environments, vehicles plan paths to the target and take precautions to minimize risks. Due to limited dynamics, bounded turning radii, and unfavorable initial conditions, they may be momentarily exposed to threats. In this study, we propose multi-objective real-time optimization based on [...] Read more.

In known environments, vehicles plan paths to the target and take precautions to minimize risks. Due to limited dynamics, bounded turning radii, and unfavorable initial conditions, they may be momentarily exposed to threats. In this study, we propose multi-objective real-time optimization based on Dubins paths for multiple vehicles. They synchronize target arrival by reasonably changing speeds and selecting paths of similar lengths. The closer the threats are to the robots and the target, the more path options are available. Risk is reduced in path planning by minimizing the duration of exposure to threats. Vehicles strike a balance between exposure to threats and travel time to targets. We use a probability-based approach to reduce the computation burden and select satisfactory paths such that vehicles synchronize target arrival reasonably far away from threats. The performances of the proposed methods are verified in several simulation examples. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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