Search Results (28)

Detecting internal defects in narrow and curved pipelines remains a significant challenge, due to the difficulty of achieving reliable defect perception under low-light conditions and generating collision-free motion trajectories. To address these challenges, this article proposes an event-aware ES-YOLO framework, and develops a pipeline defect inspection experimental environment that utilizes a hyper-redundant manipulator (HRM) to insert an event camera into the pipeline in a collision-free manner for defect inspection. First, to address the lack of datasets for event-based pipeline inspection, the ES-YOLO framework is proposed. This framework converts RGB data into an event dataset, N-neudet, which is subsequently used to train and evaluate the detection model. Concurrently, comparative experiments are conducted on steel and acrylic pipelines under three different illumination conditions. The experimental results demonstrate that, under low-light conditions, the event-based detection model significantly outperforms the RGB detection model in defect recognition rates for both types of pipelines. Second, a pipeline defect detection physical system is developed, integrating a visual perception module based on the ES-YOLO framework and a control module for the snake-like HRM. The system controls the HRM using a combination of Nonlinear Model Predictive Control (NMPC) and the Serpentine Crawling Algorithm (SCA), enabling the event camera to perform collision-free inspection within the pipeline. Finally, extensive pipeline insertion experiments are conducted to validate the feasibility and effectiveness of the proposed framework. The results demonstrate that the framework can effectively identify steel pipeline defects in a 2 Lux low-light environment, achieving a detection accuracy of 84%. Full article

As face forgery techniques, particularly the DeepFake method, progress, the imperative for effective detection of manipulations that enable hyper-realistic facial representations to mitigate security threats is emphasized. Current spatial domain approaches commonly encounter difficulties in generalizing across various forgery methods and compression artifacts, whereas frequency-based analyses exhibit promise in identifying nuanced local cues; however, the absence of global contexts impedes the capacity of detection methods to improve generalization. This study introduces a hybrid architecture that integrates Efficient-ViT and multi-level wavelet transform to dynamically merge spatial and frequency features through a dynamic adaptive multi-branch attention (DAMA) mechanism, thereby improving the deep interaction between the two modalities. We innovatively devise a joint loss function and a training strategy to address the imbalanced data issue and improve the training process. Experimental results on the FaceForensics++ and Celeb-DF (V2) have validated the effectiveness of our approach, attaining 97.07% accuracy in intra-dataset evaluations and a 74.7% AUC score in cross-dataset assessments, surpassing our baseline Efficient-ViT by 14.1% and 7.7%, respectively. The findings indicate that our approach excels in generalization across various datasets and methodologies, while also effectively minimizing feature redundancy through an innovative orthogonal loss that regularizes the feature space, as evidenced by the ablation study and parameter analysis. Full article

A novel algorithm (CP-QRRT*) is proposed for the path planning tasks of hyper-redundant manipulators (HRMs) in confined spaces, addressing the issues of unmet joint angle constraints, redundant planning paths, and long planning times present in previous algorithms. First, the PSO algorithm is introduced to optimize the random sampling process of the RRT series algorithms, enhancing the directionality of the random tree expansion. Subsequently, the method of backtracking ancestor nodes from the Quick-RRT* algorithm is combined to avoid getting trapped in local optima. Finally, a constraint module designed based on the maximum joint angle constraints of the HRM is implemented to limit the path deflection angles. Simulation experiments demonstrate that the proposed algorithm can satisfy the joint angle constraints of the HRM, and the planned paths are shorter and require less time. Full article

This review investigates the latest advancements in Multi-Robot Systems (MRSs) and soft robotics, with a particular focus on their integration and emerging opportunities. An MRS extends principles from distributed artificial intelligence and coordination frameworks, enabling efficient collaboration in robotic applications such as object manipulation, navigation, and transportation. Soft robotics employs flexible materials and biomimetic designs to improve adaptability in unstructured environments, with applications in manufacturing, sensing, actuation, and modeling. Unlike previous reviews, which often address these fields independently, this work emphasizes their integration, identifying key challenges such as nonlinear dynamics, hyper-redundant configurations, and adaptive control. This review discusses recent advancements in locomotion, coordination, and simulation, offering insights into the development of adaptive and collaborative robotic systems across diverse applications. Full article

Hyper-redundant space manipulators (HRSMs), with their extensive degrees of freedom, offer a promising solution for complex space operations such as on-orbit assembly and manipulation of non-cooperative objects. A critical challenge lies in achieving stable and effective grasping configurations, particularly when dealing with irregularly shaped objects in microgravity. This study addresses these challenges by developing a segmented hybrid impedance control architecture tailored to multi-point contact scenarios. The proposed framework reduces the contact forces and enhances object manipulation, enabling the secure handling of irregular objects and improving operational reliability. Numerical simulations demonstrate significant reductions in the contact forces during initial engagements, ensuring stable grasping and effective force regulation. The approach also enables precise trajectory tracking, robust collision avoidance, and resilience to external disturbances. The complete non-linear dynamics of the HRSM system are derived using the Kane method, incorporating both the free-space and constrained motion phases. These results highlight the practical capabilities of HRSM systems, including their potential to grasp and manipulate obstacles effectively, paving the way for applications in autonomous on-orbit servicing and assembly tasks. By integrating advanced control strategies and robust stability guarantees, this work provides a foundation for the deployment of HRSMs in real-world space operations, offering greater versatility and efficiency in complex environments. Full article

Trunk-like robots have attracted a lot of attention in the community of researchers interested in the general field of bio-inspired soft robotics, because trunk-like soft arms may offer high dexterity and adaptability very similar to elephants and potentially quite superior to traditional articulated manipulators. In view of the practical applications, the integration of a soft hydrostatic segment with a hard-articulated segment, i.e., a hybrid kinematic structure similar to the elephant’s body, is probably the best design framework. It is proposed that this integration should occur at the conceptual/cognitive level before being implemented in specific soft technologies, including the related control paradigms. The proposed modeling approach is based on the passive motion paradigm (PMP), originally conceived for addressing the degrees of freedom problem of highly redundant, articulated structures. It is shown that this approach can be naturally extended from highly redundant to hyper-redundant structures, including hybrid structures that include a hard and a soft component. The PMP model is force-based, not motion-based, and it is characterized by two main computational modules: the Jacobian matrix of the hybrid kinematic chain and a compliance matrix that maps generalized force fields into coordinated gestures of the whole-body model. It is shown how the modulation of the compliance matrix can be used for the synergy formation process, which coordinates the hyper-redundant nature of the hybrid body model and, at the same time, for the preparation of the trunk tip in view of a stable physical interaction of the body with the environment, in agreement with the general impedance–control concept. Full article

Hyper-redundant manipulators based on bionic structures offer superior dexterity due to their large number of degrees of freedom (DOFs) and slim bodies. However, controlling these manipulators is challenging because of infinite inverse kinematic solutions. In this paper, we present a novel reinforcement learning-based control method for hyper-redundant manipulators, integrating path and configuration planning. First, we introduced a deep reinforcement learning-based control method for a multi-target approach, eliminating the need for complicated reward engineering. Then, we optimized the network structure and joint space target points sampling to implement precise control. Furthermore, we designed a variable-reset cycle technique for a continuous multi-target approach without resetting the manipulator, enabling it to complete end-effector trajectory tracking tasks. Finally, we verified the proposed control method in a dynamic simulation environment. The results demonstrate the effectiveness of our approach, achieving a success rate of 98.32% with a 134% improvement using the variable-reset cycle technique. Full article

Flexible surgical robots are emerging as advanced tools for minimally invasive surgeries, offering greater versatility compared to traditional rigid robots. Unlike commercial endoscopes, the overtube should remain fixed to maintain stability, ensure a clear field of view, and allow surgical tools to perform tasks efficiently. While constant curvature bending of the overtube is sufficient for some lesions, certain lesions require the overtube to bend into specific shapes to achieve appropriate positioning. Various methods for creating different bending shapes have been proposed in previous research, typically involving connecting multiple segments. However, this approach complicates control and reduces both space and cost efficiency. This study proposed a conceptual method for adding a shaping tendon to control the bending shape and mathematically analyzed the effect of this shaping tendon, inserted along an arbitrary path in addition to the main driving tendons for constant curvature bending, on the bending shape of the hyper-redundant manipulator with rolling joints. The overall system was modeled and analyzed from an energy perspective, and the validity of the proposed mathematical modeling was verified through comparison with results obtained from physical experiments. In addition, it was identified that the design parameter determining the tendon path is a significant element in defining the bending shape of the overtube. Full article

A control method for a cable-driven robot in a teleoperation system is proposed using the hardware-in-the-loop (HIL) simulation technique. The main components of the teleoperated robotic system are a haptic device, also called a delta robot, and a cable-driven hyper-redundant (CDHR) robot. The CDHR manipulator has higher flexibility and multiple degrees of freedom (DOF), and, therefore, its inverse kinematics are complex. For this reason, the Jacobian method is used in place of the conventional method to calculate the inverse kinematics. Moreover, the two robots constituting the telerobotic system are different in terms of their mechanical structures and workspaces. Therefore, the position mapping method is applied to ensure that the two workspaces are utilized together. However, a singularity area appears when the mapping parameter is adjusted to expand the workspace. Therefore, a haptic algorithm is proposed to prevent the robot from moving into the singularity region and generate force feedback at the end-effector of the haptic device to warn the operator. Because experimental verification of this control strategy is difficult, the HIL technique is used for demonstration in this study to ensure stability and safety before implementation of the method at the experiment scale. The CDHR robot is designed using SolidWorks 2021. Then, the Simscape model is used to simulate the telerobotic system. In addition, the protocol between the haptic device and the laptop is programmed using C/C++ language to facilitate communication with the CDHR robot in MATLAB Simulink 2022a. A few trials are conducted to evaluate and demonstrate the effectiveness of the proposed method. Full article

A minimally-invasive manipulator characterized by hyper-redundant kinematics and embedded sensing modules is presented in this work. The bending angles (tilt and pan) of the robot tip are controlled through tendon-driven actuation; the transmission of the actuation forces to the tip is based on a Bowden-cable solution integrating some channels for optical fibers. The viability of the real-time measurement of the feedback control variables, through optoelectronic acquisition, is evaluated for automated bending of the flexible endoscope and trajectory tracking of the tip angles. Indeed, unlike conventional catheters and cannulae adopted in neurosurgery, the proposed robot can extend the actuation and control of snake-like kinematic chains with embedded sensing solutions, enabling real-time measurement, robust and accurate control of curvature, and tip bending of continuum robots for the manipulation of cannulae and microsurgical instruments in neurosurgical procedures. A prototype of the manipulator with a length of 43 mm and a diameter of 5.5 mm has been realized via 3D printing. Moreover, a multiple regression model has been estimated through a novel experimental setup to predict the tip angles from measured outputs of the optoelectronic modules. The sensing and control performance has also been evaluated during tasks involving tip rotations. Full article

Soft robots are interesting examples of hyper-redundancy in robotics. However, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials make modeling these robots more complicated. This study presents a geometric inverse kinematics (IK) model for trajectory tracking of multi-segment extensible soft robots, where each segment of the soft actuator is geometrically approximated with a rigid links model to reduce the complexity. In this model, the links are connected with rotary and prismatic joints, which enable both the extension and rotation of the robot. Using optimization methods, the desired configuration variables of the soft actuator for the desired end-effector positions were obtained. Furthermore, the redundancy of the robot is applied for second task applications, such as tip angle control. The model’s performance was investigated through kinematics and dynamics simulations and numerical benchmarks on multi-segment soft robots. The results showed lower computational costs and higher accuracy compared to most existing models. The method is easy to apply to multi-segment soft robots in both 2D and 3D, and it was experimentally validated on 3D-printed soft robotic manipulators. The results demonstrated the high accuracy in path following using this technique. Full article

Continuum manipulators, with their characteristics of flexibility and dexterity, have gained significant interest in various applications across industries such as inspection, manufacturing, space exploration, and medical surgery. However, because of their inherent compliance, handling payloads may prove challenging due to shape distortion and deflection. This demonstrates the need to optimize the manipulator’s stiffness. The primary objective of this work was to show the merits of sensitivity analysis in the design of flexible surgical manipulators. Such analysis can guide important design decisions and enable the more efficient use of available resources, contributing to designing more effective prototypes. A new sensitivity analysis framework based on a multi-model and a multi-method approach was proposed to achieve this. This framework was then demonstrated by studying a tendon-driven rolling contact joint hyper-redundant manipulator for transoral laser microsurgery. In this analysis, the effects of independent design parameters on the stiffness of the manipulator were examined. Then, scaled-up 3D-printed prototypes were used to validate the accuracy of the stiffness model experimentally, which enabled us to assess the outcome of the sensitivity analysis framework. The results demonstrated that only two out of five design parameters for the considered manipulator significantly impacted the device’s performance. This information could enable the designer to efficiently allocate resources toward correctly setting these two most important parameters to achieve the desired system. Overall, the proposed analysis framework is a general tool that can be applied to any design architecture, helping to develop optimal manipulators for various applications. Full article

A hyper-redundant flexible manipulator is characterized by high degree(s) of freedom (DoF), flexibility, and environmental adaptability. It has been used for missions in complex and unknown spaces, such as debris rescue and pipeline inspection, where the manipulator is not intelligent enough to face complex situations. Therefore, human intervention is required to assist in decision-making and control. In this paper, we designed an interactive navigation method based on mixed reality (MR) of a hyper-redundant flexible manipulator in an unknown space. A novel teleoperation system frame is put forward. An MR-based interface was developed to provide a virtual model of the remote workspace and virtual interactive interface, allowing the operator to observe the real-time situation from a third perspective and issue commands to the manipulator. As for environmental modeling, a simultaneous localization and mapping (SLAM) algorithm based on an RGB-D camera is applied. Additionally, a path-finding and obstacle avoidance method based on artificial potential field (APF) is introduced to ensure that the manipulator can move automatically under the artificial command in the remote space without collision. The results of the simulations and experiments validate that the system exhibits good real-time performance, accuracy, security, and user-friendliness. Full article

Structural optimisation of robotic manipulators is critical for any manipulator used in confined semi-structured environments, such as in agriculture. Many robotic manipulators utilised in semi-structured environments retain the same characteristics and dimensions as those used in fully-structured industrial environments, which have been proven to experience low dexterity and singularity issues in challenging environments due to their structural limitations. When implemented in environments other than fully-structured industrial environments, conventional manipulators are liable to singularity, joint limits and workspace obstacles. This makes them inapplicable in confined semi-structured environments, as they lack the flexibility to operate dexterously in such challenging environments. In this paper, structural optimisation of a hyper-redundant cable-driven manipulator is proposed to improve its performance in semi-structured and challenging confined spaces, such as in agricultural settings. The optimisation of the manipulator design is performed in terms of its manipulability and kinematics. The lengths of the links and the joint angles are optimised to minimise any error between the actual and desired position/orientation of the end-effector in a confined semi-structured task space, as well as to provide optimal flexibility for the manipulators to generate different joint configurations for obstacle avoidance in confined environments. The results of the optimisation suggest that the use of a redundant manipulator with rigid short links can result in performance with higher dexterity in confined, semi-structured environments, such as agricultural greenhouses. Full article

Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse kinematics of HRM is proposed in this paper: the variable dimension scaling method (VDSM), which can solve complex inverse kinematics while avoiding obstacles. Through this method, the path of the end-effector is scaled under a certain proportion and is adjusted depending on the position of the obstacle, which has good universality. The number of link angles changed is as small as possible in the process of achieving the end-effector moving along the desired path. With the redundancy of HRM, obstacle avoidance can be implemented in any environment by the proposed method. Through simulation and experiments in different environments, the above advantages of VDSM are verified. Full article