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Dynamics and Control System Design for Robot Manipulation

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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 (31 January 2025) | Viewed by 10587

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Special Issue Editor

Prof. Dr. Qirong Tang

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Guest Editor

Laboratory of Robotics and Multibody System, Tongji University, Shanghai 201804, China
Interests: robotics; artificial intelligence; mechatronics; multibody dynamics and optimization; virtual reality; metaverse

Special Issue Information

Dear Colleagues,

Robotic systems are driving technological innovation and transforming manufacturing and service industries. The key to advancing these systems lies in the exquisite design of dynamics and control mechanisms that enable robots to perform tasks with precision, adaptability, and efficiency. As the cornerstone of robotics, designing dynamics and control systems involves integrating various sensors and actuators to ensure accurate and reliable robot operations and provide essential feedback for navigation, manipulation, and interaction tasks. These sensors allow robots to perceive their environment, adapt to real-time changes, and execute complex actions autonomously.

This Special Issue aims to explore cutting-edge research and developments that drive the creation of highly capable and intelligent robotic systems. Authors are invited to submit high-quality papers on topics including (but not limited to) the following:

Robot localization and navigation.
Industrial collaborative robot
Rehabilitation robotics.
Assistive robotics.
Autonomous robots (air, land, sea, or aerospace) in unstructured environments.
Social robotics.
Human–robot interaction.
Human–robot collaboration.
Multi-agent robotic system.
Multi-legged robotic system.

Prof. Dr. Qirong Tang
Guest Editor

Manuscript Submission Information

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Keywords

robot dynamics
control systems
sensor fusion
intelligent robots
environmental perception
artificial intelligence
human–robot interaction

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Published Papers (10 papers)

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Research

27 pages, 3967 KiB

Open AccessArticle

Adaptive Super-Twisting Tracking for Uncertain Robot Manipulators Based on the Event-Triggered Algorithm

by Yajun Ma, Hui Zhao and Tao Li

Sensors 2025, 25(5), 1616; https://doi.org/10.3390/s25051616 - 6 Mar 2025

Viewed by 452

Abstract

In this study, the authors present an event-triggered control scheme for uncertain robot manipulators combined with an adaptive super-twisting algorithm to handle uncertain robot manipulator systems with unknown external uncertainties and disturbances. The proposed controller can ensure the system-tracking performance while also guaranteeing the robust stability of the system. First, an event-triggered adaptive super-twisting control (ETASTC) method for multivariable second-order nonlinear systems is proposed. In addition, unlike the implementation of periodic control, in the event-triggered method, the control signal is updated by the requirement of system stability, thus avoiding the frequent periodic execution of control tasks. Furthermore, through rigorous proof, the Zeno free execution of the triggering sequence is also ensured. Lastly, the proposed method is illustrated through numerical simulation and experimental study, and the results show that the computational cost is saved while also ensuring the desired performance of the robot system. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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20 pages, 10408 KiB

Open AccessArticle

Integration of Real Signals Acquired Through External Sensors into RoboDK Simulation of Robotic Industrial Applications

by Cozmin Cristoiu and Andrei Mario Ivan

Sensors 2025, 25(5), 1395; https://doi.org/10.3390/s25051395 - 25 Feb 2025

Viewed by 715

Abstract

Ensuring synchronization between real-world sensor data and industrial robotic simulations remains a critical challenge in digital twin and virtual commissioning applications. This study proposes an innovative method for integrating real sensor signals into RoboDK simulations, bridging the gap between virtual models and real-world dynamics. The proposed system utilizes an Arduino-based data acquisition module and a custom Python script to establish real-time communication between physical sensors and RoboDK’s simulation environment. Unlike traditional simulations that rely on predefined simulated signals or manually triggered virtual inputs, our approach enables dynamic real-time interactions based on live sensor data. The system supports both analog and digital signals and is validated through latency measurements, demonstrating an average end-to-end delay of 23.97 ms. These results confirm the feasibility of real sensor integration into RoboDK, making the system adaptable to various industrial applications. This framework provides a scalable foundation for researchers and engineers to develop enhanced simulation environments that more accurately reflect real industrial conditions. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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21 pages, 3808 KiB

Open AccessArticle

Posture Control of Hydraulic Flexible Second-Order Manipulators Based on Adaptive Integral Terminal Variable-Structure Predictive Method

by Jianliang Xu, Zhen Sui and Feng Xu

Sensors 2025, 25(5), 1351; https://doi.org/10.3390/s25051351 - 22 Feb 2025

Viewed by 534

Abstract

As operational scenarios become more complex and task demands intensify, the requirements for the intelligence and automation of manipulators in industry are increasing. This work investigates the challenge of posture tracking control for hydraulic flexible manipulators by proposing a discrete-time integral terminal sliding mode predictive control (DITSMPC) method. First, the proposed method develops a second-order dynamic model of the manipulator using the Lagrangian dynamic strategy. Second, a discrete-time sliding mode control (SMC) law based on an adaptive switching term is designed to achieve high-precision tracking control of the system. Finally, to weaken the influence of SMC buffeting on the manipulator system, the predictive time domain function is integrated into the proposed SMC law, and the delay estimation of the unknown term in the manipulator system is carried out. The DITSMPC scheme is derived and its convergence is proven. Simulation experiments comparing the DITSMPC scheme with the classical discrete-time SMC method demonstrate that the proposed scheme results in smooth torque changes in each joint of the manipulator, with the integral of torque variations being

5.22 \times 10^{3}

. The trajectory tracking errors for each joint remain within ±0.0025 rad, all of which are smaller than those of the classical scheme. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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15 pages, 5856 KiB

Open AccessArticle

Controlling a Mecanum-Wheeled Robot with Multiple Swivel Axes Controlled by Three Commands

by Yuto Nakagawa, Naoki Igo and Kiyoshi Hoshino

Sensors 2025, 25(3), 709; https://doi.org/10.3390/s25030709 - 24 Jan 2025

Viewed by 628

Abstract

The Mecanum-wheeled robot has four special wheels. It can control four wheels independently and has seven turning axes. The robot can translate in all directions and travel in curves without changing its direction by means of the control commands for turning ratio, speed, and direction of travel. However, no model has been proposed that can accurately simulate the output of the actual machine for the three types of inputs, even when the characteristics of the motor and motor driver are unknown. In this study, we synthesized and simplified transfer functions and estimated the undetermined coefficients that minimize the sum of squared errors to construct a model of the robot that can output the position and posture equivalent to those of the actual robot for the input commands for turning ratio, speed, and the direction of travel. We modeled a Mecanum-wheeled robot using the proposed modeling method and parameter determination method and compared the outputs of the real robot to the step and ramp inputs. The results showed that the errors between the two outputs were very small and accurate enough to simulate AI learning, such as reinforcement learning, using the model of the robot. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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27 pages, 10043 KiB

Open AccessArticle

An Over-Actuated Hexacopter Tilt-Rotor UAV Prototype for Agriculture of Precision: Modeling and Control

by Gabriel Oliveira Pimentel, Murillo Ferreira dos Santos, José Lima, Paolo Mercorelli and Fernanda Mara Fernandes

Sensors 2025, 25(2), 479; https://doi.org/10.3390/s25020479 - 15 Jan 2025

Cited by 1 | Viewed by 1276

Abstract

This paper focuses on the modeling, control, and simulation of an over-actuated hexacopter tilt-rotor (HTR). This configuration implies that two of the six actuators are independently tilted using servomotors, which provide high maneuverability and reliability. This approach is predicted to maintain zero pitch throughout the trajectory and is expected to improve the aircraft’s steering accuracy. This arrangement is particularly beneficial for precision agriculture (PA) applications where accurate monitoring and management of crops are critical. The enhanced maneuverability allows for precise navigation in complex vineyard environments, enabling the unmanned aerial vehicle (UAV) to perform tasks such as aerial imaging and crop health monitoring. The employed control architecture consists of cascaded proportional (P)-proportional, integral and derivative (PID) controllers using the successive loop closure (SLC) method on the five controlled degrees of freedom (DoFs). Simulated results using Gazebo demonstrate that the HTR achieves stability and maneuverability throughout the flight path, significantly improving precision agriculture practices. Furthermore, a comparison of the HTR with a traditional hexacopter validates the proposed approach. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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25 pages, 12643 KiB

Open AccessArticle

A Fuzzy Control Strategy for Multi-Goal Autonomous Robot Navigation

by Stavros Stavrinidis, Paraskevi Zacharia and Elias Xidias

Sensors 2025, 25(2), 446; https://doi.org/10.3390/s25020446 - 14 Jan 2025

Cited by 3 | Viewed by 1124

Abstract

This paper addresses the complex problem of multi-goal robot navigation, framed as an NP-hard traveling salesman problem (TSP), in environments with both static and dynamic obstacles. The proposed approach integrates a novel path planning algorithm based on the Bump-Surface concept to optimize the shortest collision-free path among static obstacles, while a Genetic Algorithm (GA) is employed to determine the optimal sequence of goal points. To manage static or dynamic obstacles, two fuzzy controllers are developed: one for real-time path tracking and another for dynamic obstacle avoidance. This dual-controller system enables the robot to adaptively adjust its trajectory while ensuring collision-free navigation in unpredictable environments. The integration of fuzzy logic with TSP-based path planning and real-time dynamic obstacle handling represents a significant advancement in autonomous robot navigation. Simulations conducted in CoppeliaSim validate the effectiveness of the proposed method, demonstrating robust navigation and obstacle avoidance in realistic environments. This work provides a comprehensive framework for solving multi-goal navigation tasks by incorporating TSP optimization with dynamic, real-time path adjustments. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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18 pages, 6842 KiB

Open AccessArticle

Haptic Shared Control Framework with Interaction Force Constraint Based on Control Barrier Function for Teleoperation

by Wenlei Qin, Haoran Yi, Zhibin Fan and Jie Zhao

Sensors 2025, 25(2), 405; https://doi.org/10.3390/s25020405 - 11 Jan 2025

Viewed by 851

Abstract

Current teleoperated robotic systems for retinal surgery cannot effectively control subtle tool-to-tissue interaction forces. This limitation may lead to patient injury caused by the surgeon’s mistakes. To improve the safety of retinal surgery, this paper proposes a haptic shared control framework for teleoperation based on a force-constrained supervisory controller. The supervisory controller leverages Control Barrier Functions (CBFs) and the interaction model to modify teleoperated inputs when they are deemed unsafe. This method ensures that the interaction forces at the slave robot’s end-effector remain within the safe range without the robot’s dynamic model and the safety margin. Additionally, the master robot provides haptic feedback to enhance the surgeon’s situational awareness during surgery, reducing the risk of misjudgment. Finally, simulated membrane peeling experiments are conducted in a controlled intraocular surgical environment using a teleoperated robotic system controlled by a non-expert. The experimental results demonstrate that the proposed control framework significantly reduces the rate of force constraint violation. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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21 pages, 1265 KiB

Open AccessArticle

Leveraging Environmental Contact and Sensor Feedback for Precision in Robotic Manipulation

by Jan Šifrer and Tadej Petrič

Sensors 2024, 24(21), 7006; https://doi.org/10.3390/s24217006 - 31 Oct 2024

Viewed by 1298

Abstract

This paper investigates methods that leverage physical contact between a robot’s structure and its environment to enhance task performance, with a primary emphasis on improving precision. Two main approaches are examined: solving the inverse kinematics problem and employing quadratic programming, which offers computational efficiency by utilizing forward kinematics. Additionally, geometrical methods are explored to simplify robot assembly and reduce the complexity of control calculations. These approaches are implemented on a physical robotic platform and evaluated in real-time applications to assess their effectiveness. Through experimental evaluation, this study aims to understand how environmental contact can be utilized to enhance performance across various conditions, offering valuable insights for practical applications in robotics. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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19 pages, 3640 KiB

Open AccessArticle

Recognition of Chinese Electronic Medical Records for Rehabilitation Robots: Information Fusion Classification Strategy

by Jiawei Chu, Xiu Kan, Yan Che, Wanqing Song, Kudreyko Aleksey and Zhengyuan Dong

Sensors 2024, 24(17), 5624; https://doi.org/10.3390/s24175624 - 30 Aug 2024

Viewed by 1645

Abstract

Named entity recognition is a critical task in the electronic medical record management system for rehabilitation robots. Handwritten documents often contain spelling errors and illegible handwriting, and healthcare professionals frequently use different terminologies. These issues adversely affect the robot’s judgment and precise operations. Additionally, the same entity can have different meanings in various contexts, leading to category inconsistencies, which further increase the system’s complexity. To address these challenges, a novel medical entity recognition algorithm for Chinese electronic medical records is developed to enhance the processing and understanding capabilities of rehabilitation robots for patient data. This algorithm is based on a fusion classification strategy. Specifically, a preprocessing strategy is proposed according to clinical medical knowledge, which includes redefining entities, removing outliers, and eliminating invalid characters. Subsequently, a medical entity recognition model is developed to identify Chinese electronic medical records, thereby enhancing the data analysis capabilities of rehabilitation robots. To extract semantic information, the ALBERT network is utilized, and BILSTM and MHA networks are combined to capture the dependency relationships between words, overcoming the problem of different meanings for the same entity in different contexts. The CRF network is employed to determine the boundaries of different entities. The research results indicate that the proposed model significantly enhances the recognition accuracy of electronic medical texts by rehabilitation robots, particularly in accurately identifying entities and handling terminology diversity and contextual differences. This model effectively addresses the key challenges faced by rehabilitation robots in processing Chinese electronic medical texts, and holds important theoretical and practical value. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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21 pages, 23176 KiB

Open AccessArticle

Improved YOLOv5 Network for High-Precision Three-Dimensional Positioning and Attitude Measurement of Container Spreaders in Automated Quayside Cranes

by Yujie Zhang, Yangchen Song, Luocheng Zheng, Octavian Postolache, Chao Mi and Yang Shen

Sensors 2024, 24(17), 5476; https://doi.org/10.3390/s24175476 - 23 Aug 2024

Viewed by 1016

Abstract

For automated quayside container cranes, accurate measurement of the three-dimensional positioning and attitude of the container spreader is crucial for the safe and efficient transfer of containers. This paper proposes a high-precision measurement method for the spreader’s three-dimensional position and rotational angles based on a single vertically mounted fixed-focus visual camera. Firstly, an image preprocessing method is proposed for complex port environments. The improved YOLOv5 network, enhanced with an attention mechanism, increases the detection accuracy of the spreader’s keypoints and the container lock holes. Combined with image morphological processing methods, the three-dimensional position and rotational angle changes of the spreader are measured. Compared to traditional detection methods, the single-camera-based method for three-dimensional positioning and attitude measurement of the spreader employed in this paper achieves higher detection accuracy for spreader keypoints and lock holes in experiments and improves the operational speed of single operations in actual tests, making it a feasible measurement approach. Full article

(This article belongs to the Special Issue Dynamics and Control System Design for Robot Manipulation)

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