Robotics

22 pages, 6085 KiB

Open AccessArticle

A Sliding Mode Approach to Vector Field Path Following for a Fixed-Wing UAV

by Luca Pugi, Lorenzo Franchi, Samuele Favilli and Giuseppe Mattei

Robotics 2025, 14(1), 7; https://doi.org/10.3390/robotics14010007 - 9 Jan 2025

Viewed by 1155

Unmanned aerial vehicle (UAV) technology has recently experienced increasing development, leading to the creation of a wide variety of autonomous solutions. In this paper, a guidance strategy for straight and orbital paths following fixed-wing small UAVs is presented. The proposed guidance algorithm is [...] Read more.

Unmanned aerial vehicle (UAV) technology has recently experienced increasing development, leading to the creation of a wide variety of autonomous solutions. In this paper, a guidance strategy for straight and orbital paths following fixed-wing small UAVs is presented. The proposed guidance algorithm is based on a reference vector field as desired, with 16 courses for the UAV to follow. A sliding mode approach is implemented to improve the robustness and effectiveness, and the asymptotic convergence of the aircraft to the desired trajectory in the presence of constant wind disturbances is proved according to Lyapunov. The algorithm exploits the banking dynamics and generates reference signals for the inner-loop aileron control. A MATLAB&Simulink^® simulation environment is used to verify the performance and robustness of the compared guidance algorithms. This high-fidelity model considers the six-degrees-of-freedom (DoF) whole-flight dynamics of the UAV and it is based on experimental flight test data to implement the aerodynamic behavior. Full article

(This article belongs to the Section Aerospace Robotics and Autonomous Systems)

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23 pages, 5366 KiB

Open AccessArticle

Evaluation of the Cyber-Physical System State Under Destructive Impact Conditions Based on a Comprehensive Analysis of Parameters

by Anton Mogilny, Elena Basan and Alexey Nekrasov

Robotics 2025, 14(1), 6; https://doi.org/10.3390/robotics14010006 - 8 Jan 2025

Cited by 1 | Viewed by 1029

Abstract

This manuscript proposes a method for analyzing the stability of the behavior of a cyber-physical system (CPS) under conditions of potential destructive impact, considering the tasks it performs, which does not require labeled sets of abnormal data. The considered CPS has an autonomous [...] Read more.

This manuscript proposes a method for analyzing the stability of the behavior of a cyber-physical system (CPS) under conditions of potential destructive impact, considering the tasks it performs, which does not require labeled sets of abnormal data. The considered CPS has an autonomous decision-making system. The method was formalized in terms of the Markov decision-making process. Proposed metrics for assessing CPS behavior based on changes in its parameters were defined. They allowed classifying the operating mode into three classes: normal, abnormal, and uncertain. Evaluation results prove the efficiency of the proposed method. Despite the proposed method being tested on an unmanned vehicle (UV), it can also be applied to other CPSs, primarily to autonomous mobile robots (AMRs). Full article

(This article belongs to the Special Issue UAV Systems and Swarm Robotics)

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26 pages, 34170 KiB

Open AccessArticle

Navigating ALICE: Advancements in Deployable Docking and Precision Detection for AUV Operations

by Yevgeni Gutnik, Nir Zagdanski, Sharon Farber, Tali Treibitz and Morel Groper

Robotics 2025, 14(1), 5; https://doi.org/10.3390/robotics14010005 - 31 Dec 2024

Viewed by 1181

Abstract

Autonomous Underwater Vehicles (AUVs) operate independently using onboard batteries and data storage, necessitating periodic recovery for battery recharging and data transfer. Traditional surface-based launch and recovery (L&R) operations pose significant risks to personnel and equipment, particularly in adverse weather conditions. Subsurface docking stations [...] Read more.

Autonomous Underwater Vehicles (AUVs) operate independently using onboard batteries and data storage, necessitating periodic recovery for battery recharging and data transfer. Traditional surface-based launch and recovery (L&R) operations pose significant risks to personnel and equipment, particularly in adverse weather conditions. Subsurface docking stations provide a safer alternative but often involve complex fixed installations and costly acoustic positioning systems. This work introduces a comprehensive docking solution featuring the following two key innovations: (1) a novel deployable docking station (DDS) designed for rapid deployment from vessels of opportunity, operating without active acoustic transmitters; and (2) an innovative sensor fusion approach that combines the AUV’s onboard forward-looking sonar and camera data. The DDS comprises a semi-submersible protective frame and a subsurface, heave-compensated docking component equipped with backlit visual markers, an electromagnetic (EM) beacon, and an EM lifting device. This adaptable design is suitable for temporary installations and in acoustically sensitive or covert operations. The positioning and guidance system employs a multi-sensor approach, integrating range and azimuth data from the sonar with elevation data from the vision camera to achieve precise 3D positioning and robust navigation in varying underwater conditions. This paper details the design considerations and integration of the AUV system and the docking station, highlighting their innovative features. The proposed method was validated through software-in-the-loop simulations, controlled seawater pool experiments, and preliminary open-sea trials, including several docking attempts. While further sea trials are planned, current results demonstrate the potential of this solution to enhance AUV operational capabilities in challenging underwater environments while reducing deployment complexity and operational costs. Full article

(This article belongs to the Special Issue Navigation Systems of Autonomous Underwater and Surface Vehicles)

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15 pages, 2425 KiB

Open AccessArticle

Online Self-Supervised Learning for Accurate Pick Assembly Operation Optimization

by Sergio Valdés, Marco Ojer and Xiao Lin

Robotics 2025, 14(1), 4; https://doi.org/10.3390/robotics14010004 - 30 Dec 2024

Viewed by 1128

Abstract

The demand for flexible automation in manufacturing has increased, incorporating vision-guided systems for object grasping. However, a key challenge is in-hand error, where discrepancies between the actual and estimated positions of an object in the robot’s gripper impact not only the grasp but [...] Read more.

The demand for flexible automation in manufacturing has increased, incorporating vision-guided systems for object grasping. However, a key challenge is in-hand error, where discrepancies between the actual and estimated positions of an object in the robot’s gripper impact not only the grasp but also subsequent assembly stages. Corrective strategies used to compensate for misalignment can increase cycle times or rely on pre-labeled datasets, offline training, and validation processes, delaying deployment and limiting adaptability in dynamic industrial environments. Our main contribution is an online self-supervised learning method that automates data collection, training, and evaluation in real time, eliminating the need for offline processes. Building on this, our system collects real-time data during each assembly cycle, using corrective strategies to adjust the data and autonomously labeling them via a self-supervised approach. It then builds and evaluates multiple regression models through an auto machine learning implementation. The system selects the best-performing model to correct the misalignment and dynamically chooses between corrective strategies and the learned model, optimizing the cycle times and improving the performance during the cycle, without halting the production process. Our experiments show a significant reduction in the cycle time while maintaining the performance. Full article

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

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18 pages, 1226 KiB

Open AccessArticle

Quadrotor Trajectory Planning with Tetrahedron Partitions and B-Splines in Unknown and Dynamic Environments

by Jiayu Men and Jesús Requena Carrión

Robotics 2025, 14(1), 3; https://doi.org/10.3390/robotics14010003 - 30 Dec 2024

Viewed by 866

Abstract

Trajectory planning is a key task in unmanned aerial vehicle navigation systems. Although trajectory planning in the presence of obstacles is a well-understood problem, unknown and dynamic environments still present significant challenges. In this paper, we present a trajectory planning method for unknown [...] Read more.

Trajectory planning is a key task in unmanned aerial vehicle navigation systems. Although trajectory planning in the presence of obstacles is a well-understood problem, unknown and dynamic environments still present significant challenges. In this paper, we present a trajectory planning method for unknown and dynamic environments that explicitly incorporates the uncertainty about the environment. Assuming that the position of obstacles and their instantaneous movement are available, our method represents the environment uncertainty as a dynamic map that indicates the probability that a region might be occupied by an obstacle in the future. The proposed method first divides the free space into non-overlapping tetrahedral partitions using Delaunay triangulation. Then, a topo-graph that describes the topology of the free space and incorporates the uncertainty of the environment is created. Using this topo-graph, an initial path and a safe flight corridor are obtained. The initial safe flight corridor provides a sequence of control points that we use to optimize clamped B-spline trajectories by formulating a quadratic programming problem with safety and smoothness constraints. Using computer simulations, we show that our algorithm can successfully find a collision-free and uncertainty-aware trajectory in an unknown and dynamic environment. Furthermore, our method can reduce the computational burden caused by moving obstacles during trajectory replanning. Full article

(This article belongs to the Special Issue UAV Systems and Swarm Robotics)

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15 pages, 5191 KiB

Open AccessArticle

Determining the Proper Force Parameters for Robotized Pipetting Devices Used in Automated Polymerase Chain Reaction (PCR)

by Melania-Olivia Sandu, Valentin Ciupe, Corina-Mihaela Gruescu, Robert Kristof, Carmen Sticlaru and Elida-Gabriela Tulcan

Robotics 2025, 14(1), 2; https://doi.org/10.3390/robotics14010002 - 28 Dec 2024

Viewed by 1044

Abstract

This study aims to provide a set of experimentally determined forces needed for gripping operations related to a robotically manipulated microliter manual pipette. The experiments are conducted within the scope of automated sample processing for polymerase chain reaction (PCR) analysis in small-sized to [...] Read more.

This study aims to provide a set of experimentally determined forces needed for gripping operations related to a robotically manipulated microliter manual pipette. The experiments are conducted within the scope of automated sample processing for polymerase chain reaction (PCR) analysis in small-sized to medium-sized laboratories where dedicated automated equipment is absent and where procedures are carried out manually. Automation is justified by the requirement for increased efficiency and to eliminate possible errors generated by lab technicians. The test system comprises an industrial robot; a dedicated custom gripper assembly necessary for the pipette; pipetting tips; and mechanical holders for tubes with chemical substances and genetic material. The selected approach is to measure forces using the robot’s built-in force–torque sensor while controlling and limiting the pipette’s gripping force and the robot’s pushing force. Because the manipulation of different materials requires the attachment and discarding of tips to and from the pipette, the operator’s perceived tip release force is also considered. Full article

(This article belongs to the Special Issue Selected Papers from MEDER 2024: Advances in Mechanism Design for Robotics)

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18 pages, 11046 KiB

Open AccessArticle

Inverse and Forward Kinematics and CAD-Based Simulation of a 5-DOF Delta-Type Parallel Robot with Actuation Redundancy

by Pavel Laryushkin, Anton Antonov, Alexey Fomin and Oxana Fomina

Robotics 2025, 14(1), 1; https://doi.org/10.3390/robotics14010001 - 27 Dec 2024

Cited by 1 | Viewed by 1346

Abstract

This article introduces a novel modification of a Delta-type parallel robot. The robot has five degrees of freedom and provides its end-effector with a 3T2R motion pattern (three translational and two rotational degrees of freedom). The fifth degree of freedom (rotation) is kinematically [...] Read more.

This article introduces a novel modification of a Delta-type parallel robot. The robot has five degrees of freedom and provides its end-effector with a 3T2R motion pattern (three translational and two rotational degrees of freedom). The fifth degree of freedom (rotation) is kinematically decoupled from the other four motions, and it is controlled by two drives. Thus, the proposed robot has a redundant actuation. In this article, we present an algorithm to solve the inverse kinematics of this robot and apply it to a path modeling example of a spiral-like trajectory. Numerical simulations illustrate the algorithm and show how the actuated coordinates change along the considered trajectory. Forward kinematics follows next, and an approach is introduced to determine all end-effector configurations for the specified displacements in the actuated joints. A numerical example presents four assembly modes of the robot corresponding to four real solutions of the forward kinematic problem. Finally, this article demonstrates a computer-aided design and analysis of the proposed robot: we describe a procedure for analyzing inverse kinematics and calculating actuation torques. This study forms the basis for the future manufacturing and experimental analysis of a robot prototype. Full article

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

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Robotics, Volume 14, Issue 1 (January 2025) – 7 articles

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