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Distributed Monitoring of Moving Thermal Targets Using Unmanned Aerial Vehicles and Gaussian Mixture Models
Autonomous, Collaborative, and Confined Infrastructure Assessment with Purpose-Built Mega-Joey Robots
Model-Based Predictive Control for Position and Orientation Tracking in a Multilayer Architecture for a Three-Wheeled Omnidirectional Mobile Robot

Journal Description

Robotics

Robotics is an international, peer-reviewed, open access journal on robotics published monthly online by MDPI. The IFToMM is affiliated with Robotics and its members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, ESCI (Web of Science), dblp, Inspec, and other databases.
Journal Rank: JCR - Q2 (Robotics) / CiteScore - Q1 (Control and Optimization)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 21.8 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Journal Cluster of Mechanical Manufacturing and Automation Control: Aerospace, Automation, Drones, Journal of Manufacturing and Materials Processing, Machines, Robotics and Technologies.

Impact Factor: 3.3 (2024); 5-Year Impact Factor: 3.8 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2218-6581

Latest Articles

49 pages, 15124 KiB

Open AccessArticle

Flexible Constraint-Based Controller Framework for Ros_Control

by Miguel Prada, Asier Fernandez, Anthony Remazeilles and Joseph McIntyre

Robotics 2025, 14(8), 109; https://doi.org/10.3390/robotics14080109 - 11 Aug 2025

Generating robot behaviors in dynamic real-world situations generally requires the programming of multiple, often redundant degrees of freedom to meet multiple goals governing the desired motions. In this work, we propose a constraint-based controller specification methodology. A novel declarative language is used to [...] Read more.

Generating robot behaviors in dynamic real-world situations generally requires the programming of multiple, often redundant degrees of freedom to meet multiple goals governing the desired motions. In this work, we propose a constraint-based controller specification methodology. A novel declarative language is used to combine semantically specialized building blocks into composite controllers. This description is automatically transformed at runtime into an executable form, which can automatically leverage multiple threads to parallelize computations whenever possible. Enabling runtime definition of controller topologies out of declarative descriptions not only reduces the work required to develop such controllers, but it also allows one to dynamically synthesize new controllers based on higher-level task planners or by user interaction through Graphical User Interfaces (GUIs). Our solution adds new functionality to the Robot Operating System (ROS)/ros_control ecosystem, where robot behaviors are typically achieved by deploying single-objective, off-the-shelf controllers for tasks like following joint trajectories, executing interpolated point-to-point motions in Cartesian space, or for basic compliant behaviors. Our proposed constraint-based framework enhances ros_control by providing the means to easily construct composite controllers from existing primary elements using our design language. Building on top of the ros_control infrastructure facilitates the usage of our controller with a wide range of supported robots and enables quick integration with the existing ROS ecosystem. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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14 pages, 18726 KiB

Open AccessArticle

Safe Autonomous UAV Target-Tracking Under External Disturbance, Through Learned Control Barrier Functions

by Promit Panja, Madan Mohan Rayguru and Sabur Baidya

Robotics 2025, 14(8), 108; https://doi.org/10.3390/robotics14080108 - 3 Aug 2025

Ensuring the safe operation of Unmanned Aerial Vehicles (UAVs) is crucial for both mission-critical and safety-critical tasks. In scenarios where UAVs must track airborne targets, they need to follow the target’s path while maintaining a safe distance, even in the presence of unmodeled [...] Read more.

Ensuring the safe operation of Unmanned Aerial Vehicles (UAVs) is crucial for both mission-critical and safety-critical tasks. In scenarios where UAVs must track airborne targets, they need to follow the target’s path while maintaining a safe distance, even in the presence of unmodeled dynamics and environmental disturbances. This paper presents a novel collision avoidance strategy for dynamic quadrotor UAVs during target-tracking missions. We propose a safety controller that combines a learning-based Control Barrier Function (CBF) with standard sliding mode feedback. Our approach employs a neural network that learns the true CBF constraint, accounting for wind disturbances, while the sliding mode controller addresses unmodeled dynamics. This unified control law ensures safe leader-following behavior and precise trajectory tracking. By leveraging a learned CBF, the controller offers improved adaptability to complex and unpredictable environments, enhancing both the safety and robustness of the system. The effectiveness of our proposed method is demonstrated through the AirSim platform using the PX4 flight controller. Full article

(This article belongs to the Special Issue Applications of Neural Networks in Robot Control)

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16 pages, 2448 KiB

Open AccessArticle

A Body-Powered Underactuated Prosthetic Finger Driven by MCP Joint Motion

by Worathris Chungsangsatiporn, Chaiwuth Sithiwichankit, Ratchatin Chancharoen, Ronnapee Chaichaowarat, Nopdanai Ajavakom and Gridsada Phanomchoeng

Robotics 2025, 14(8), 107; https://doi.org/10.3390/robotics14080107 - 31 Jul 2025

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting [...] Read more.

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article

(This article belongs to the Section Neurorobotics)

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26 pages, 6831 KiB

Open AccessArticle

Human–Robot Interaction and Tracking System Based on Mixed Reality Disassembly Tasks

by Raúl Calderón-Sesmero, Adrián Lozano-Hernández, Fernando Frontela-Encinas, Guillermo Cabezas-López and Mireya De-Diego-Moro

Robotics 2025, 14(8), 106; https://doi.org/10.3390/robotics14080106 - 30 Jul 2025

Disassembly is a crucial process in industrial operations, especially in tasks requiring high precision and strict safety standards when handling components with collaborative robots. However, traditional methods often rely on rigid and sequential task planning, which makes it difficult to adapt to unforeseen [...] Read more.

Disassembly is a crucial process in industrial operations, especially in tasks requiring high precision and strict safety standards when handling components with collaborative robots. However, traditional methods often rely on rigid and sequential task planning, which makes it difficult to adapt to unforeseen changes or dynamic environments. This rigidity not only limits flexibility but also leads to prolonged execution times, as operators must follow predefined steps that do not allow for real-time adjustments. Although techniques like teleoperation have attempted to address these limitations, they often hinder direct human–robot collaboration within the same workspace, reducing effectiveness in dynamic environments. In response to these challenges, this research introduces an advanced human–robot interaction (HRI) system leveraging a mixed-reality (MR) interface embedded in a head-mounted device (HMD). The system enables operators to issue real-time control commands using multimodal inputs, including voice, gestures, and gaze tracking. These inputs are synchronized and processed via the Robot Operating System (ROS2), enabling dynamic and flexible task execution. Additionally, the integration of deep learning algorithms ensures precise detection and validation of disassembly components, enhancing accuracy. Experimental evaluations demonstrate significant improvements, including reduced task completion times, enhanced operator experience, and compliance with strict adherence to safety standards. This scalable solution offers broad applicability for general-purpose disassembly tasks, making it well-suited for complex industrial scenarios. Full article

(This article belongs to the Special Issue Robot Teleoperation Integrating with Augmented Reality)

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18 pages, 16316 KiB

Open AccessArticle

AntGrip—Boosting Parallel Plate Gripper Performance Inspired by the Internal Hairs of Ant Mandibles

by Mohamed Sorour and Barbara Webb

Robotics 2025, 14(8), 105; https://doi.org/10.3390/robotics14080105 - 30 Jul 2025

Ants use their mandibles—effectively a two-finger gripper—for a wide range of grasping activities. Here, we investigate whether mimicking the internal hairs found on ant mandibles can improve performance of a two-finger parallel plate robot gripper. With bin-picking applications in mind, the gripper fingers [...] Read more.

Ants use their mandibles—effectively a two-finger gripper—for a wide range of grasping activities. Here, we investigate whether mimicking the internal hairs found on ant mandibles can improve performance of a two-finger parallel plate robot gripper. With bin-picking applications in mind, the gripper fingers are long and slim, with interchangeable soft gripping pads that can be hairy or hairless. A total of 2400 video-documented experiments have been conducted, comparing hairless to hairy pads with different hair patterns. Simply by adding hairs, the grasp success rate was increased by at least

29 %

, and the number of objects that remain securely gripped during manipulation more than doubled. This result not only advances the state of the art in grasping technology, but also provides novel insight into the mechanical role of mandible hairs in ant biology. Full article

(This article belongs to the Section Intelligent Robots and Mechatronics)

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20 pages, 2108 KiB

Open AccessReview

Underwater Polarized Light Navigation: Current Progress, Key Challenges, and Future Perspectives

by Mingzhi Chen, Yuan Liu, Daqi Zhu, Wen Pang and Jianmin Zhu

Robotics 2025, 14(8), 104; https://doi.org/10.3390/robotics14080104 - 29 Jul 2025

Underwater navigation remains constrained by technological limitations, driving the exploration of alternative approaches such as polarized light-based systems. This review systematically examines advances in polarized navigation from three perspectives. First, the principles of atmospheric polarization navigation are analyzed, with their operational mechanisms, advantages, [...] Read more.

Underwater navigation remains constrained by technological limitations, driving the exploration of alternative approaches such as polarized light-based systems. This review systematically examines advances in polarized navigation from three perspectives. First, the principles of atmospheric polarization navigation are analyzed, with their operational mechanisms, advantages, and inherent constraints dissected. Second, innovations in bionic polarization multi-sensor fusion positioning are consolidated, highlighting progress beyond conventional heading-direction extraction. Third, emerging underwater polarization navigation techniques are critically evaluated, revealing that current methods predominantly adapt atmospheric frameworks enhanced by advanced filtering to mitigate underwater interference. A comprehensive synthesis of underwater polarization modeling methodologies is provided, categorizing physical, data-driven, and hybrid approaches. Through rigorous analysis of studies, three persistent barriers are identified: (1) inadequate polarization pattern modeling under dynamic cross-media conditions; (2) insufficient robustness against turbidity-induced noise; (3) immature integration of polarization vision with sonar/IMU (Inertial Measurement Unit) sensing. Targeted research directions are proposed, including adaptive deep learning models, multi-spectral polarization sensing, and bio-inspired sensor fusion architectures. These insights establish a roadmap for developing reliable underwater navigation systems that transcend current technological boundaries. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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21 pages, 6018 KiB

Open AccessArticle

Model-Based Design of the 5-DoF Light Industrial Robot

by Yongping Shi, Tianbing Ma, Hao Wang, Tao Zhang, Xin Zhang, Huapeng Wu and Ming Li

Robotics 2025, 14(8), 103; https://doi.org/10.3390/robotics14080103 - 29 Jul 2025

With the application and rapid development of light industrial robots, it is vital to accelerate the prototype design to fulfill the demands of shortening the robot’s production cycle, owing to rapid update iterations. Since the traditional design method cannot intuitively and efficiently check [...] Read more.

With the application and rapid development of light industrial robots, it is vital to accelerate the prototype design to fulfill the demands of shortening the robot’s production cycle, owing to rapid update iterations. Since the traditional design method cannot intuitively and efficiently check the deficiencies in the design preparation, the secondary design iterations will result in higher equipment costs, longer design cycles, and lower development efficiency. The MBD (model-based design), a full 3D (three-dimensional) design and manufacturing method, is proposed to swiftly finish the prototype design for solving the above problems. Firstly, the robot design preparation is completed with the design requirements to generate a robot 3D model. Secondly, several design methods are used: (i) the rapid prototyping, which includes the joint component verification and selection to further optimize the 3D model; (ii) the robot kinematics algorithm, which provides a theoretical foundation for the 3D model design; (iii) the robot kinematics simulation, which verifies the correctness of the kinematics algorithm. Finally, the feasibility of the MBD is verified by the robot prototype and the motion control system test. Taking the MBD to design a 5-DoF (five-degrees-of-freedom) robot as an example, the joint verification and selection are finished quickly and accurately to build the robot prototype without the need for secondary design processing, and the kinematic algorithm verified by the co-simulation platform can be used directly in the actual motion control of the robot prototype, which accelerates the development of the robot motion control system. Full article

(This article belongs to the Section Industrial Robots and Automation)

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18 pages, 2335 KiB

Open AccessArticle

MLLM-Search: A Zero-Shot Approach to Finding People Using Multimodal Large Language Models

by Angus Fung, Aaron Hao Tan, Haitong Wang, Bensiyon Benhabib and Goldie Nejat

Robotics 2025, 14(8), 102; https://doi.org/10.3390/robotics14080102 - 28 Jul 2025

Robotic search of people in human-centered environments, including healthcare settings, is challenging, as autonomous robots need to locate people without complete or any prior knowledge of their schedules, plans, or locations. Furthermore, robots need to be able to adapt to real-time events that [...] Read more.

Robotic search of people in human-centered environments, including healthcare settings, is challenging, as autonomous robots need to locate people without complete or any prior knowledge of their schedules, plans, or locations. Furthermore, robots need to be able to adapt to real-time events that can influence a person’s plan in an environment. In this paper, we present MLLM-Search, a novel zero-shot person search architecture that leverages multimodal large language models (MLLM) to address the mobile robot problem of searching for a person under event-driven scenarios with varying user schedules. Our approach introduces a novel visual prompting method to provide robots with spatial understanding of the environment by generating a spatially grounded waypoint map, representing navigable waypoints using a topological graph and regions by semantic labels. This is incorporated into an MLLM with a region planner that selects the next search region based on the semantic relevance to the search scenario and a waypoint planner that generates a search path by considering the semantically relevant objects and the local spatial context through our unique spatial chain-of-thought prompting approach. Extensive 3D photorealistic experiments were conducted to validate the performance of MLLM-Search in searching for a person with a changing schedule in different environments. An ablation study was also conducted to validate the main design choices of MLLM-Search. Furthermore, a comparison study with state-of-the-art search methods demonstrated that MLLM-Search outperforms existing methods with respect to search efficiency. Real-world experiments with a mobile robot in a multi-room floor of a building showed that MLLM-Search was able to generalize to new and unseen environments. Full article

(This article belongs to the Section Intelligent Robots and Mechatronics)

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32 pages, 5721 KiB

Open AccessReview

Control Strategies for Two-Wheeled Self-Balancing Robotic Systems: A Comprehensive Review

by Huaqiang Zhang and Norzalilah Mohamad Nor

Robotics 2025, 14(8), 101; https://doi.org/10.3390/robotics14080101 - 26 Jul 2025

Two-wheeled self-balancing robots (TWSBRs) are underactuated, inherently nonlinear systems that exhibit unstable dynamics. Due to their structural simplicity and rich control challenges, TWSBRs have become a standard platform for validating and benchmarking various control algorithms. This paper presents a comprehensive and structured review [...] Read more.

Two-wheeled self-balancing robots (TWSBRs) are underactuated, inherently nonlinear systems that exhibit unstable dynamics. Due to their structural simplicity and rich control challenges, TWSBRs have become a standard platform for validating and benchmarking various control algorithms. This paper presents a comprehensive and structured review of control strategies applied to TWSBRs, encompassing classical linear approaches such as PID and LQR, modern nonlinear methods including sliding mode control (SMC), model predictive control (MPC), and intelligent techniques such as fuzzy logic, neural networks, and reinforcement learning. Additionally, supporting techniques such as state estimation, observer design, and filtering are discussed in the context of their importance to control implementation. The evolution of control theory is analyzed, and a detailed taxonomy is proposed to classify existing works. Notably, a comparative analysis section is included, offering practical guidelines for selecting suitable control strategies based on system complexity, computational resources, and robustness requirements. This review aims to support both academic research and real-world applications by summarizing key methodologies, identifying open challenges, and highlighting promising directions for future development. Full article

(This article belongs to the Section Industrial Robots and Automation)

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16 pages, 10372 KiB

Open AccessArticle

PRONOBIS: A Robotic System for Automated Ultrasound-Based Prostate Reconstruction and Biopsy Planning

by Matija Markulin, Luka Matijević, Janko Jurdana, Luka Šiktar, Branimir Ćaran, Toni Zekulić, Filip Šuligoj, Bojan Šekoranja, Tvrtko Hudolin, Tomislav Kuliš, Bojan Jerbić and Marko Švaco

Robotics 2025, 14(8), 100; https://doi.org/10.3390/robotics14080100 - 22 Jul 2025

This paper presents the PRONOBIS project, an ultrasound-only, robotically assisted, deep learning-based system for prostate scanning and biopsy treatment planning. The proposed system addresses the challenges of precise prostate segmentation, reconstruction and inter-operator variability by performing fully automated prostate scanning, real-time CNN-transformer-based image [...] Read more.

This paper presents the PRONOBIS project, an ultrasound-only, robotically assisted, deep learning-based system for prostate scanning and biopsy treatment planning. The proposed system addresses the challenges of precise prostate segmentation, reconstruction and inter-operator variability by performing fully automated prostate scanning, real-time CNN-transformer-based image processing, 3D prostate reconstruction, and biopsy needle position planning. Fully automated prostate scanning is achieved by using a robotic arm equipped with an ultrasound system. Real-time ultrasound image processing utilizes state-of-the-art deep learning algorithms with intelligent post-processing techniques for precise prostate segmentation. To create a high-quality prostate segmentation dataset, this paper proposes a deep learning-based medical annotation platform, MedAP. For precise segmentation of the entire prostate sweep, DAF3D and MicroSegNet models are evaluated, and additional image post-processing methods are proposed. Three-dimensional visualization and prostate reconstruction are performed by utilizing the segmentation results and robotic positional data, enabling robust, user-friendly biopsy treatment planning. The real-time sweep scanning and segmentation operate at 30 Hz, which enable complete scan in 15 to 20 s, depending on the size of the prostate. The system is evaluated on prostate phantoms by reconstructing the sweep and by performing dimensional analysis, which indicates 92% and 98% volumetric accuracy on the tested phantoms. Three-dimansional prostate reconstruction takes approximately 3 s and enables fast and detailed insight for precise biopsy needle position planning. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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13 pages, 2559 KiB

Open AccessArticle

An AI Approach to Markerless Augmented Reality in Surgical Robots

by Abhishek Shankar, Luay Jawad and Abhilash Pandya

Robotics 2025, 14(7), 99; https://doi.org/10.3390/robotics14070099 - 19 Jul 2025

This paper examines the integration of markerless augmented reality (AR) within the da Vinci Surgical Robot, utilizing artificial intelligence (AI) for improved precision. The main challenge in creating AR for these systems is the small size (5 mm diameter) of the cameras used. [...] Read more.

This paper examines the integration of markerless augmented reality (AR) within the da Vinci Surgical Robot, utilizing artificial intelligence (AI) for improved precision. The main challenge in creating AR for these systems is the small size (5 mm diameter) of the cameras used. Traditional camera-calibration approaches produce significant errors when used for miniature cameras. Further, the use of external markers can be obstructive and inaccurate in dynamic surgical environments. The study focuses on overcoming these limitations of traditional AR methods by employing advanced neural networks for camera calibration and real-time image processing. We demonstrate the use of a dense neural network to reduce the total projection error by directly learning the mapping of a 3D point to a 2D image plane. The results show a median error of 7 pixels (1.4 mm) when using a neural network, as compared to an error of 50 pixels (10 mm) when using a more traditional approach involving camera calibration and robot kinematics. This approach not only enhances the accuracy of AR for surgical procedures but also offers a more seamless integration with existing robotic platforms. These research findings underscore the potential of AI in revolutionizing AR applications in medical robotics and other teleoperated systems, promising efficient and safer interventions. Full article

(This article belongs to the Section Medical Robotics and Service Robotics)

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15 pages, 1795 KiB

Open AccessArticle

Minimum-Energy Trajectory Planning for an Underactuated Serial Planar Manipulator

by Domenico Dona’, Jason Bettega, Iacopo Tamellin, Paolo Boscariol and Roberto Caracciolo

Robotics 2025, 14(7), 98; https://doi.org/10.3390/robotics14070098 - 18 Jul 2025

Underactuated robotic systems are appealing for industrial use due to their reduced actuator number, which lowers energy consumption and system complexity. Underactuated systems are, however, often affected by residual vibrations. This paper addresses the challenge of generating energy-optimal trajectories while imposing theoretical null [...] Read more.

Underactuated robotic systems are appealing for industrial use due to their reduced actuator number, which lowers energy consumption and system complexity. Underactuated systems are, however, often affected by residual vibrations. This paper addresses the challenge of generating energy-optimal trajectories while imposing theoretical null residual (and yet practical low) vibration in underactuated systems. The trajectory planning problem is cast as a constrained optimal control problem (OCP) for a two-degree-of-freedom revolute–revolute planar manipulator. The proposed method produces energy-efficient motion while limiting residual vibrations under motor torque limitations. Experiments compare the proposed trajectories to input shaping techniques (ZV, ZVD, NZV, NZVD). Results show energy savings that range from 12% to 69% with comparable and negligible residual oscillations. Full article

(This article belongs to the Special Issue Adaptive and Nonlinear Control of Robotics)

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21 pages, 6802 KiB

Open AccessArticle

Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0

by Ilias Chouridis, Gabriel Mansour, Asterios Chouridis, Vasileios Papageorgiou, Michel Theodor Mansour and Apostolos Tsagaris

Robotics 2025, 14(7), 97; https://doi.org/10.3390/robotics14070097 - 15 Jul 2025

Collaborative robots are vital in Industry 5.0 operations. They are utilized to perform tasks in collaboration with humans or other robots to increase overall production efficiency and execute complex tasks. Aiming at a comprehensive approach to assembly processes and highlighting new applications of [...] Read more.

Collaborative robots are vital in Industry 5.0 operations. They are utilized to perform tasks in collaboration with humans or other robots to increase overall production efficiency and execute complex tasks. Aiming at a comprehensive approach to assembly processes and highlighting new applications of collaborative robots, this paper presents the development of a digital twin (DT) for the design, monitoring, optimization and simulation of robots’ deployment in assembly cells. The DT integrates information from both the physical and virtual worlds to design the trajectory of collaborative robots. The physical information about the industrial environment is replicated within the DT in a computationally efficient way that aligns with the requirements of the path planning algorithm and the DT’s objectives. An enhanced artificial fish swarm algorithm (AFSA) is utilized for the 4D path planning optimization, taking into account dynamic and static obstacles. Finally, the proposed framework is utilized for the examination of a case in which four industrial robotic arms are collaborating for the assembly of an industrial component. Full article

(This article belongs to the Special Issue Robot Teleoperation Integrating with Augmented Reality)

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22 pages, 4827 KiB

Open AccessArticle

Development of a Multifunctional Mobile Manipulation Robot Based on Hierarchical Motion Planning Strategy and Hybrid Grasping

by Yuning Cao, Xianli Wang, Zehao Wu and Qingsong Xu

Robotics 2025, 14(7), 96; https://doi.org/10.3390/robotics14070096 - 15 Jul 2025

A mobile manipulation robot combines the navigation capability of unmanned ground vehicles and manipulation advantage of robotic arms. However, the development of a mobile manipulation robot is challenging due to the integration requirement of numerous heterogeneous subsystems. In this paper, we propose a [...] Read more.

A mobile manipulation robot combines the navigation capability of unmanned ground vehicles and manipulation advantage of robotic arms. However, the development of a mobile manipulation robot is challenging due to the integration requirement of numerous heterogeneous subsystems. In this paper, we propose a multifunctional mobile manipulation robot by integrating perception, mapping, navigation, object detection, and grasping functions into a seamless workflow to conduct search-and-fetch tasks. To realize navigation and collision avoidance in complex environments, a new hierarchical motion planning strategy is proposed by fusing global and local planners. Control Lyapunov Function (CLF) and Control Barrier Function (CBF) are employed to realize path tracking and to guarantee safety during navigation. The convolutional neural network and the gripper’s kinematic constraints are adopted to construct a learning-optimization hybrid grasping algorithm to generate precise grasping poses. The efficiency of the developed mobile manipulation robot is demonstrated by performing indoor fetching experiments, showcasing its promising capabilities in real-world applications. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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27 pages, 6183 KiB

Open AccessArticle

A Cartesian Parallel Mechanism for Initial Sonography Training

by Mykhailo Riabtsev, Jean-Michel Guilhem, Victor Petuya, Mónica Urizar and Med Amine Laribi

Robotics 2025, 14(7), 95; https://doi.org/10.3390/robotics14070095 - 10 Jul 2025

This paper presents the development and analysis of a novel 6-DOF Cartesian parallel mechanism intended for use as a haptic device for initial sonography training. The system integrates a manipulator designed for delivering force feedback in five degrees of freedom; however, in the [...] Read more.

This paper presents the development and analysis of a novel 6-DOF Cartesian parallel mechanism intended for use as a haptic device for initial sonography training. The system integrates a manipulator designed for delivering force feedback in five degrees of freedom; however, in the current stage, only mechanical architecture and kinematic validation have been conducted. Future enhancements will focus on implementing and evaluating closed-loop force control to enable complete haptic feedback. To assess the kinematic performance of the mechanism, a detailed kinematic model was developed, and both the Kinematic Conditioning Index (KCI) and Global Conditioning Index (GCI) were computed to evaluate the system’s dexterity. A trajectory simulation was conducted to validate the mechanism’s movement, using motion patterns typical in sonography procedures. Quasi-static analysis was performed to study the transmission of force and torque for generating realistic haptic feedback, critical for simulating real-life sonography. The simulation results showed consistent performance, with dexterity and torque distribution confirming the suitability of the mechanism for haptic applications in sonography training. Additionally, structural analysis verified the robustness of key components under expected loads. In order to validate the proposed design, the prototype was constructed using a combination of aluminum components and 3D-printed ABS parts, with Igus^® linear guides for precise motion. The outcomes of this study provide a foundation for the further development of a low-cost, effective sonography training system. Full article

(This article belongs to the Section Medical Robotics and Service Robotics)

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27 pages, 2922 KiB

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

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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40 pages, 5657 KiB

Open AccessReview

Optimizing Coalition Formation Strategies for Scalable Multi-Robot Task Allocation: A Comprehensive Survey of Methods and Mechanisms

by Krishna Arjun, David Parlevliet, Hai Wang and Amirmehdi Yazdani

Robotics 2025, 14(7), 93; https://doi.org/10.3390/robotics14070093 - 2 Jul 2025

In practical applications, the utilization of multi-robot systems (MRS) is extensive and spans various domains such as search and rescue operations, mining operations, agricultural tasks, and warehouse management. The surge in demand for MRS has prompted extensive exploration of Multi-Robot Task Allocation (MRTA). [...] Read more.

In practical applications, the utilization of multi-robot systems (MRS) is extensive and spans various domains such as search and rescue operations, mining operations, agricultural tasks, and warehouse management. The surge in demand for MRS has prompted extensive exploration of Multi-Robot Task Allocation (MRTA). Researchers have devised a range of methodologies to tackle MRTA problems, aiming to achieve optimal solutions, yet there remains room for further enhancements in this field. Among the complex challenges in MRTA, the identification of an optimal coalition formation (CF) solution stands out as one of the (Nondeterministic Polynomial) NP-hard problems. CF pertains to the effective coordination and grouping of agents or robots for efficient task execution, achieved through optimal task allocation. In this context, this paper delivers a succinct overview of dynamic task allocation and CF strategies. It conducts a comprehensive examination of diverse strategies employed for MRTA. The analysis encompasses the advantages, disadvantages, and comparative assessments of these strategies with a focus on CF. Furthermore, this study introduces a novel classification system for prominent task allocation methods and compares these methods with simulation analysis. The fidelity and effectiveness of the proposed CF approach are substantiated through comparative assessments and simulation studies. Full article

(This article belongs to the Section AI in Robotics)

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14 pages, 2424 KiB

Open AccessArticle

Grasping Task in Teleoperation: Impact of Virtual Dashboard on Task Quality and Effectiveness

by Antonio Di Tecco, Daniele Leonardis, Antonio Frisoli and Claudio Loconsole

Robotics 2025, 14(7), 92; https://doi.org/10.3390/robotics14070092 - 30 Jun 2025

This research study investigates the impact of a virtual dashboard on the quality of task execution in robotic teleoperation. More specifically, this study investigates how a virtual dashboard improves user awareness and grasp precision in a teleoperated pick-and-place task by providing users with [...] Read more.

This research study investigates the impact of a virtual dashboard on the quality of task execution in robotic teleoperation. More specifically, this study investigates how a virtual dashboard improves user awareness and grasp precision in a teleoperated pick-and-place task by providing users with critical information in real-time. An experiment was conducted with 30 participants in a robotic teleoperated task to measure their task performance in two different experimental conditions: a control group used conventional interfaces, and an experimental group utilized the virtual dashboard with additional information. Research findings indicate that integrating a virtual dashboard improves grasping accuracy, reduces user fatigue, and speeds up task completion, thereby improving task effectiveness and the quality of the experience. Full article

(This article belongs to the Special Issue Extended Reality and AI Empowered Robots)

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22 pages, 7125 KiB

Open AccessArticle

Planar Inverse Statics and Path Planning for a Tendon-Driven Discrete Continuum Robot

by Yeoun-Jae Kim and Daehan Wi

Robotics 2025, 14(7), 91; https://doi.org/10.3390/robotics14070091 - 30 Jun 2025

This study addresses the clinical requirements of a transoral surgery-assisting continuum robot. This application requires both high bendability and stiffness in order to ensure precise positioning and stable fixation of surgical tools. To meet these needs, we developed a tendon-driven discrete continuum robot [...] Read more.

This study addresses the clinical requirements of a transoral surgery-assisting continuum robot. This application requires both high bendability and stiffness in order to ensure precise positioning and stable fixation of surgical tools. To meet these needs, we developed a tendon-driven discrete continuum robot unit featuring a ball–socket joint and superelastic Nitinol rods. One to three serially connected robot units were tested by applying proximal tendon tension (

T_{l}

) in the range of 100–1000 g while distal tension (

T_{s}

) was continuously increased to induce bending. During bending, the curves were interpolated using third-order to fifth-order polynomials at discrete

T_{l}

levels. The interpolated inverse statics were validated experimentally and compared with finite element simulations using ANSYS. Furthermore, we propose a planar path planning algorithm and numerically evaluate it for a three-unit robot following an arc-shaped trajectory. The inverse statics successfully captured the nonlinear bending behavior of the tendon-driven robot. Validation experiments showed average angular errors of 2.7%, 6.6%, and 5.3% for one, two, and three connected units, respectively. The proposed path planning method achieved an average positional deviation from the reference trajectory ranging from 0.95 mm to 19.77 mm. This work presents a practical and generalizable experimental mapping framework for the inverse statics of tendon-driven discrete continuum robots, avoiding the need for complex analytical models. Full article

(This article belongs to the Special Issue Development of Biomedical Robotics)

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18 pages, 8647 KiB

Open AccessArticle

An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning

by Yizhe Jia, Yong Cai, Jun Zhou, Hui Hu, Xuesheng Ouyang, Jinlong Mo and Hao Dai

Robotics 2025, 14(7), 90; https://doi.org/10.3390/robotics14070090 - 29 Jun 2025

The advancement of mobile robot technology has made path planning a necessary condition for autonomous navigation, but traditional algorithms have issues with efficiency and reliability in dynamic and unstructured environments. This study proposes a Dynamic Hybrid A* (DHA*)–Adaptive Dynamic Window Approach (ADA-DWA) fusion [...] Read more.

The advancement of mobile robot technology has made path planning a necessary condition for autonomous navigation, but traditional algorithms have issues with efficiency and reliability in dynamic and unstructured environments. This study proposes a Dynamic Hybrid A* (DHA*)–Adaptive Dynamic Window Approach (ADA-DWA) fusion algorithm for efficient and reliable path planning in dynamic unstructured environments. This paper improves the A* algorithm by introducing a dynamic hybrid heuristic function, optimizing the selection of key nodes, and enhancing the neighborhood search strategy, and collaboratively optimizes the search efficiency and path smoothness through curvature optimization. On this basis, the local planning layer introduces a self-adjusting weight-adaptive system in the DWA framework to dynamically optimize the speed, sampling distribution, and trajectory evaluation metrics, achieving a balance between obstacle avoidance and environmental adaptability. The proposed fusion algorithm’s comprehensive advantages over traditional methods in key operational indicators, including path optimality, computational efficiency, and obstacle avoidance capability, have been widely verified through numerical simulations and physical platforms. This method successfully resolves the inherent trade-off between efficiency and reliability in complex robot navigation scenarios, providing enhanced operational robustness for practical applications ranging from industrial logistics to field robots. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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