Robotic Mechanisms Research Articles

Transendoscopic flexible parallel continuum robotic mechanism for bimanual endoscopic submucosal dissection

In endoscopic submucosal dissection (ESD), the gastrointestinal (GI) tract warrants the surgical instruments to navigate through a long, narrow and tortuous endoscope. This poses a great challenge in developing ESD instruments with small dimensions, flexibility, and high distal dexterity. In this work, we propose the first Transendoscopic Flexible Parallel Continuum Robotic mechanism to develop a miniature dexterous flexible-stiff-balanced Wrist (FPCW). Besides, it can steer multifunctional instruments of diameters 2.5 mm to 3.5 mm, including the electrosurgical knife, injection needle, and forceps. Our FPCW instruments are adaptable to commercially available dual-channel endoscopes (diameter: <12 mm, channel width: 2.8 mm and around 3.8 mm). Furthermore, we develop a surgical telerobotic system, called DREAMS (Dual-arm Robotic Endoscopic Assistant for Minimally Invasive Surgery), by using our smallest FPCW instruments for bimanual ESD procedures. First, we conduct a series of experiments to determine the FPCW’s design and kinematics parameters and to verify the mechanical properties of the FPCW instruments’ prototypes, including workspace, stiffness, strength, and teleoperation accuracy. Second, we validate the functionality of the FPCW instruments through ex-vivo tests by performing ESD steps on porcine stomachs. Finally, we perform an invivo test on a live porcine model and showcase that our developed DREAMS can be teleoperated intuitively to perform bimanual ESD efficiently with an average dissection speed of 108.95 mm2/min at the greater curvature in gastric body, which demonstrates that our DREAMS has satisfactory maneuverability as well as accuracy and is more competitive than counterpart robotic systems.

A general method for the manipulability analysis of serial robot manipulators

Manipulability quantification and evaluation of robot manipulators plays an important role in robotic mechanism design, motion planning, and control. In this article, a general methodology of using manipulability polytopes to characterize the manipulator’s capability to generate velocities, forces, and accelerations at the end-effector is proposed. This methodology can be used to determine the kinematic, mechanical, and dynamic manipulability of both redundant and nonredundant serial manipulators, where influences of gravity, joint velocities and accelerations, and end-effector payload on the dynamic manipulability are incorporated into the derivation of the manipulability polytopes. Since the manipulability polytope is the feasible region defined by all the joint constraints, the proposed method is suitable for solving the problems including both symmetric and asymmetric joint constraints. Furthermore, a systematic architecture and detailed procedures for performance computation with respect to different types of manipulability of serial robot manipulators are presented. Two typical application examples, respectively, for two and three degree-of-freedom planar manipulators are given to illustrate the correctness and capability of the proposed methodology.

An Invariant Representation of Coupler Curves Using a Variational AutoEncoder: Application to Path Synthesis of Four-Bar Mechanisms

Abstract This paper focuses on the representation and synthesis of coupler curves of planar mechanisms using a deep neural network. While the path synthesis of planar mechanisms is not a new problem, the effective representation of coupler curves in the context of neural networks has not been fully explored. This study compares four commonly used features or representations of four-bar coupler curves: Fourier descriptors, wavelets, point coordinates, and images. The results demonstrate that these diverse representations can be unified using a generative AI framework called variational autoencoder (VAE). This study shows that a VAE can provide a standalone representation of a coupler curve, regardless of the input representation, and that the compact latent dimensions of the VAE can be used to describe coupler curves of four-bar linkages. Additionally, a new approach that utilizes a VAE in conjunction with a fully connected neural network to generate dimensional parameters of four-bar linkage mechanisms is proposed. This research presents a novel opportunity for the automated conceptual design of mechanisms for robots and machines.

Design and Kinematic Modeling of a Soft Continuum Telescopic Arm for the Self-Assembly Mechanism of a Modular Robot.

In recent years, the development of mining robots has grown significantly, offering improved efficiency and safety in hazardous environments. However, there is still room for improvement in adaptability, scalability, and overall performance. The ROBOMINERS project, funded by the European Union's Horizon 2020 Research and Innovation Program, aims to facilitate Europe's access to mineral resources applying disruptive robotic concepts. One such concept is resilience, which can be achieved providing modular mining robots with the ability to reconfigure during operation. To address this challenge, this article presents the development and kinematic modeling of a soft, telescopic, continuum arm integrated into a modular robot. The arm serves as a mechanical interface for coupling different robotic modules or tools following the principle of the car crane. With a fully 3D-printed design, the arm features two sections of variable length that are driven by an innovative actuation method based on soft racks. It provides a 6 degrees of freedom (DoF) motion. The arm kinematic models are obtained by backbone parameterization assuming constant curvature and independent bending between sections for forward kinematics and applying a machine learning-based approach for inverse kinematics. The models are validated through the evaluation of two trajectories, measuring the deviation in each DoF and rack extension. Furthermore, a demonstration of the arm's coupling procedure between two robotic modules and one possible configuration of the robotic system showcases its functionality.

A Forward Solution Algorithm of 6RUS Parallel Mechanism Based on Dual Quaternion Method

The 6RUS parallel manipulator is a highly versatile and widely used robotic mechanism with six degrees of freedom. Its intricate kinematic structure and its capability to perform complex motion tasks have garnered significant research interest in recent years. The kinematic analysis of the 6RUS mechanism plays a crucial role in understanding its operational characteristics and optimizing its performance for various applications. In this paper, we present a state-of-the-art kinematic algorithm for the 6RUS parallel manipulator. Our algorithm is aimed at addressing the challenges associated with accurately determining the pose and motion of the end-effector relative to the base, considering the complexity of the mechanism’s architecture. By leveraging advanced mathematical modeling techniques and utilizing efficient computational algorithms, our proposed algorithm offers improved accuracy, efficiency, and robustness in determining the kinematic parameters of the 6RUS mechanism. The key contributions of this work include the development of a comprehensive forward and inverse kinematic model for the 6RUS parallel manipulator, incorporating the effects of joint constraints, singularities, and workspace limitations. We also present a detailed analysis of the algorithm’s performance in comparison to existing approaches, demonstrating its superiority in terms of computational efficiency and accuracy. The proposed kinematic algorithm holds significant potential for enhancing the design, control, and trajectory planning of 6RUS parallel manipulators. It provides a solid foundation for advanced applications such as robotic surgery, industrial automation, and virtual reality systems. The results presented in this paper contribute to the growing body of knowledge in parallel manipulator research and pave the way for future developments in the field.

Retracted: Hardware Realization of Kinematic Mechanism and Control System of Multifunctional Industrial Robot

Retracted: Hardware Realization of Kinematic Mechanism and Control System of Multifunctional Industrial Robot

Nonlinear disturbance observer-based robust predefined time tracking and vibration suppression control for the rigid-flexible coupled robotic mechanisms with large beam-deformations

Nonlinear disturbance observer-based robust predefined time tracking and vibration suppression control for the rigid-flexible coupled robotic mechanisms with large beam-deformations

Implementation of L4 Automation for Patient-Specific Quality Assurance Using the AUTOFRAME Platform and a Robotic Mechanism

The AUTOFRAME platform has been previously developed for automating clinical workflows and has achieved L3 automation for patient-specific quality assurance (PSQA). The aim of this study is to further develop the platform to achieve L4 automation, which extends AUTOFRAME to operate Varian's control console (VCC) for the linear accelerator. The goal is to automate all PSQA operations outside of the treatment room. The automated stages, listed in Table 1, are ranging from L0 to L5. The current study focuses on L4 automation of PSQA, which uses a 6-axis robot arm to control buttons on the VCC. The robotic arm is mounted on a custom frame that is attached onto the VCC to maintain its relative position. The arm is controlled through python scripts, which is run on a raspberry pi and communicates with the AUTOFRAME platform via the PyFlow and AutoFlow subsystems. This integration allows the robotic arm to receive commands from AutoFlow and execute them through PyFlow, activating real-time button-pressing actions. The integrated L4 system was tested using real PSQA verification plans, which involved a minimum of 4 actions and a maximum of 9 actions on the VCC, including a couch kick that required overriding the couch position. The results showed that the 6-axis arm was able to correctly execute the action groups and guide the robotic arm to consistently press and hold each button with sufficient force and accuracy. All buttons on the VCC, including the Motion-enable, Preparing, Readying, and Delivering buttons, were correctly pushed and held according to the PSQA steps. The system successfully delivered all beams without interruption, and all beam delivery data was collected by the detector for PSQA analysis. The study has further developed the AUTOFRAME platform for L4 automation of PSQA procedures can be achieved. The robotic arm is capable of pushing all required buttons, eliminating all human interactions on the VCC. When combined with previous L0-L3 automations, this will move towards full automation of PSQA procedures. Future work will focus on improving the system's flexibility, stability, and extending its operations to other QA tasks.

Research on obstacle-surmounting mechanism of transformable robot

With the innovation and advancement of technology, the research in the field of transformable robots have shown explosive growth and are moving towards intelligence and diversification. Transformable robots can transform their mobile mechanisms according to different terrains for obstacle surmounting, with high flexibility, strong adaptability, and scalability. Thus, transformable robots are widely used in fields such as reconnaissance, rescue, and military. In this article, the characteristics of different obstacle surmounting mechanisms of transformable robots are analysed. Based on three traditional obstacle surmounting mechanisms: wheeled, tracked, and legged, this article introduces the concepts and advantages of combined obstacle surmounting mechanisms and emerging soft and biomimetic robot obstacle surmounting mechanisms. After elaborating on the current research status and partial applications of composite transformable obstacle surmounting robots, the key technologies and difficulties in the research of obstacle surmounting mechanisms for transformable robots are summarized. In addition, this article provides prospects for the application of transformable obstacle surmounting robots in medical and agricultural fields.

A Decoupling Method for Successive Robot Rotation Based on Time Domain Instantaneous Euler Angle

In the present study, a novel time domain decoupling method was proposed for the multiple successive rotations of different kinds of robots. This is achieved through the utilization of instantaneous Euler angles. For a general parallel mechanism, the Plücker coordinates of the intersection line of the before and after rotation plane are determined through the reciprocal product principle of screw theory. Additionally, the angle between these two rotation planes is defined as the instantaneous Euler angle. The analysis of the general parallel mechanism was used as an example to illustrate the solution method of the instantaneous Euler angle. To investigate the intrinsic relationship between the instantaneous Euler angle and the conventional Euler angle, the mathematical mapping relationship and the difference between the instantaneous Euler angle and the two kinds of Euler angles (Z-Y-X and Z-Y-Z) were explored, respectively. Simulations of a 3-sps-s parallel mechanism and a robotic arm were employed to illustrate the superiority of the instantaneous Euler angle. The findings showed that the instantaneous Euler angle exhibited enhanced temporal consistency compared to the conventional Euler angle. Further, it is better suited for accurately describing the decoupled rotation of robotic systems. The proposed approach is also generally applicable to robot performance evaluation, mechanism design, and other relevant fields.

Type synthesis of worm-like planar tensegrity mobile robot

It is a tough task to figure out how to employ a small number of actuators to give a mobile robot multiple locomotion modes. This work suggested an unique type synthesis approach for tensegrity robots with few actuators and multi-locomotion mode by unit-splicing, focusing on robotic mechanisms and aiming at three locomotion modes that worms may realize (earthworm-like, inchworm, and tumbling locomotion). The static and deformation stability were used to screen out all of the tensegrity planar units that might achieve the desired locomotion modes. On this basis, traditional tensegrity structures are modified and springs are introduced in order to decrease the number of actuators. Then, all the tensegrity mechanisms that could be driven by two motors and realize the three locomotion modes were acquired by the splicing of units and merging of cables, and the value ranges of the parameters of robotic members that could satisfy the stability criteria were presented. Following the type synthesis results, a configuration was chosen, and a prototype was created. The experiment proved the viability of the type synthesis approach by demonstrating that the robot can implement the three locomotion modes with just two actuators.

Automated Object Sorting System with Real-Time Image Processing and Robotic Gripper Mechanism Control

This work represents an industrial sorting system where image processing is accompanied using a pick-and-place robotic gripper. The sorting of objects is done based on their shape and color. Here the color and shape of different objects are identified using image processing. For this, a webcam is used to capture images of the object in real-time and then process them via a digital computer. Python programming language is used for image processing in this work. After successfully identifying the color and shape of an object, the object is picked and placed at the desired position using the robotic gripper. Controlling the gripper mechanism is also executed using the Python programming language. It is controlled using the Arduino Uno microcontroller and a few DC servo motors. The gripper can move from 0° to 180°. The objects are brought in front of the camera using a belt conveyor system. After the complete fabrication and assembly, 4 objects of different shapes and colors are used to sort objects at 4 different angles. The objects are picked from 90° and is sorted in either 0°, 45°, 135°, or 180° position. This research work not only gives information about robotics but also can help industries sort complex objects automatically without any human interaction.

Pretty Darn Good Control: When are Approximate Solutions Better than Approximate Models.

Existing methods for optimal control struggle to deal with the complexity commonly encountered in real-world systems, including dimensionality, process error, model bias and data heterogeneity. Instead of tackling these system complexities directly, researchers have typically sought to simplify models to fit optimal control methods. But when is the optimal solution to an approximate, stylized model better than an approximate solution to a more accurate model? While this question has largely gone unanswered owing to the difficulty of finding even approximate solutions for complex models, recent algorithmic and computational advances in deep reinforcement learning (DRL) might finally allow us to address these questions. DRL methods have to date been applied primarily in the context of games or robotic mechanics, which operate under precisely known rules. Here, we demonstrate the ability for DRL algorithms using deep neural networks to successfully approximate solutions (the "policy function" or control rule) in a non-linear three-variable model for a fishery without knowing or ever attempting to infer a model for the process itself. We find that the reinforcement learning agent discovers a policy that outperforms both constant escapement and constant mortality policies-the standard family of policies considered in fishery management. This DRL policy has the shape of a constant escapement policy whose escapement values depend on the stock sizes of other species in the model.

Realization Method of Stable Continuous Steering Jumping for a Bioinspired Jerboa Robot

AbstractThe continuous jumping of bioinspired robots in 3D spaces can greatly improve its motion flexibility, which is one of the highlights of research on jumping robots. However, most existing jumping robots can only move in a plane, and achieving stable continuous steering jumping is difficult. In this study, a realization method of stable continuous steering jumping for a bioinspired jerboa robot is proposed. On the basis of the jumping mechanism of the jerboa, the robot mechanism model is established, and the factors affecting motion feasibility and performance are analyzed in detail. Then, mathematical models of the stability indices of the robot jumping on uneven ground with redundant driving are established. Based on the proposed improved bee colony algorithm, the motion parameters and driving parameters can be determined. Simulation results show that the robot can realize stable continuous steering jumping in different terrains along the expected trajectory, thus proving the feasibility of the method proposed in this study. This study provides a theoretical reference for the high‐speed flexible motion of legged robots in 3D spaces.

Fault detection and state estimation in robotic automatic control using machine learning

In the commercial and industrial sectors, automatic robotic control mechanisms, which include robots, end effectors, and anchors containing components, are often utilized to enhance service quality. Robotic systems must be installed in manufacturing lines for a variety of industrial purposes, which also increases the risk of a robot, end controller, and/or device malfunction. According to its automated regulation, this may hurt people and other items in the workplace in addition to resulting in a reduction in quality operation. With today's advanced systems and technology, security and stability are crucial. Hence, the system is equipped with fault management abilities for the identification of developing defects and assessment of their influence on the system's activity in the upcoming utilizing fault diagnostic methodologies. To provide adaptive control, fault detection, and state estimation for robotic automated systems intended to function dependably in complicated contexts, efficient techniques are described in this study. This paper proposed a fault detection and state estimation using Accelerated Gradient Descent based support vector machine (AGDSVM) and gaussian filter (GF) in automatic control systems. The Proposed system is called (AGDSVM + GF). The proposed system is evaluated with the following metrics accuracy, fault detection rate, state estimation rate, computation time, error rate, and energy consumption. The result shows that the proposed system is effective in fault detection and state estimation and provides intelligent control automatic control.

On Research of Cable Tension Distribution Algorithm for Four Cables - Three DOF Planar Cable-Driven Parallel Robot

One of the main concerns in controlling the cable-driven parallel robot (CDPR) mechanism is dealing with the distribution of tension on each cable, which is critical to the operation of the entire cable system. It can be said that adjusting the cable tension will determine the power consumption of the motors and the stiffness of the structure. Therefore, the problem that needs to be solved is how to handle the cable tension when the end-effector moves throughout the entire workspace. The tension of each cable needs to be adjusted properly to ensure it remains the same. Moment and force act in a static state, keeping the kinematic position of the end moving platform from being deflected and the main purpose is to ensure that the robot achieves a rigid state and eliminates vibration when moving. Because of that essential demand, this article will refer to the Quadratic programming algorithm to solve the problem of tension distribution for the Planar Cable-Driven Parallel Robot consisting of 4 cables with 3 degrees of freedom. This article will be the foundation for applying this algorithm to an 8-cable robot with 6 degrees of freedom (Spatial Cable-Driven Parallel Robot for example). At the same time, in this article, the simulation results for the algorithm will also be presented in this paper.

Effect of Robotic Pile-Up Mechanism on Cooperative Transportation for Versatile Objects

In recent years, cooperative transportation systems using multiple mobile robots have been studied. The advantage will be to transport objects that cannot be dealt with by a single robot and transport them by using smaller robots. Although cooperative transportation by a group of robots has been studied, the conventional transportation targets are limited to objects whose posture is stable. In this paper, we propose a system in which robots pile up on each other to support an object, aiming at a system for more versatile object transportation, including unstable objects. After deriving the conditions by modeling the support system in object transportation, we verify the transporting performance including the robotic pile-up effect through actual robot experiments.

Kinematic modeling and motion control of a parallel robotic antenna pedestal

AbstractThis paper deals with kinematic modeling and motion control of a novel antenna pedestal based on parallel robotic mechanism. Its active joints are two sliders equipped with DC motors on a circular rail. The synchronous and asynchronous motions of the two sliders enable the antenna to rotate in azimuth and pitch. In order to solve the problem of trajectory deviation caused by nonlinear friction and other uncertain disturbances, the structure of the antenna is described at the beginning, and then, the kinematic model is established based on geometry method. Then, the fuzzy PI (FPI) control system is designed based on the position feedback of the driving slider to realize the trajectory tracking of the desired curve. Finally, the parameters of the FPI controller are optimized and validated by Simulink simulation experiments. The tracking performance and the effectiveness of the control algorithm on prototype are verified by experiments of typical trajectory following control.

Selection/control concurrent optimization of BLDC motors for industrial robots.

This paper aims to concurrently select and control off-the-shelf BLDC motors of industrial robots by using a synergistic model-based approach. The BLDC motors are considered with trapezoidal back-emf, where the three-phase (a,b,c) dynamics of motors are modeled in a mechatronic powertrain model of the robot for the selection and control problem, defining it as a multi-objective dynamic optimization problem with static and dynamic constraints. Since the mechanical and electrical actuators' parameters modify the robot's performance, the selection process considers the actuators' parameters, their control input, operational limits, and the mechanical output to the transmission of the robot joints. Then, three objective functions are to be minimized, the motor's energy consumption, the tracking error, and the total weight of installed motors on the robot mechanism. The control parameterization approach via a cascade controller with PI controllers for actuators' voltage and a PID controller for actuators' torque is used to solve the multi-objective dynamic optimization problem. Based on simulations of the closed-loop system, a Pareto front is obtained to examine trade-offs among the objective functions before implementing any actuators in the existing robotic system. The proposed method is tested on an experimental platform to verify its effectiveness. The performance of an industrial robot with the actuators originally installed is compared with the results obtained by the synergic approach. The results of this comparison show that 10.85% of electrical power can be saved, and the trajectory tracking error improved up to 57.41% using the proposed methodology.

Actuation Mechanisms and Applications for Soft Robots: A Comprehensive Review

Soft robots, which exhibit distinguishing features in terms of compliance, adaptability, and safety, have been expansively adopted in various niche applications. For soft robots, innovative actuators have been designed based on smart materials enabling the robots to perform flexible and versatile functions, whereas extra spaces and accessories to accommodate motors and power devices have been eliminated to achieve structural optimisation. Herein, different types of actuation mechanisms for soft robots are summarised to reflect the state-of-the-art research and applications. Major characteristics of the actuation mechanisms are updated. Design methodologies of the actuation mechanisms are discussed in detail. Furthermore, their advantages, disadvantages, and application potential are compared and summarised. In the end, based on our knowledge and understanding, new thoughts and recommendations to further develop the actuation mechanisms are put forward. This review is useful to support the conclusion that, through incorporating actuation mechanisms and advanced intelligent technologies, soft robots tend to create disruptive innovations in applications.