Model Of Robot Research Articles

G2-MonoDepth: A General Framework of Generalized Depth Inference From Monocular RGB+X Data.

Monocular depth inference is a fundamental problem for scene perception of robots. Specific robots may be equipped with a camera plus an optional depth sensor of any type and located in various scenes of different scales, whereas recent advances derived multiple individual sub-tasks. It leads to additional burdens to fine-tune models for specific robots and thereby high-cost customization in large-scale industrialization. This article investigates a unified task of monocular depth inference, which infers high-quality depth maps from all kinds of input raw data from various robots in unseen scenes. A basic benchmark G2-MonoDepth is developed for this task, which comprises four components: (a) a unified data representation RGB+X to accommodate RGB plus raw depth with diverse scene scale/semantics, depth sparsity ([0%, 100%]) and errors (holes/noises/blurs), (b) a novel unified loss to adapt to diverse depth sparsity/errors of input raw data and diverse scales of output scenes, (c) an improved network to well propagate diverse scene scales from input to output, and (d) a data augmentation pipeline to simulate all types of real artifacts in raw depth maps for training. G2-MonoDepth is applied in three sub-tasks including depth estimation, depth completion with different sparsity, and depth enhancement in unseen scenes, and it always outperforms SOTA baselines on both real-world data and synthetic data.

Dynamic Modeling and Improved Nonlinear Model Predictive Control of a Free-Floating Dual-Arm Space Robot

With the increasing demand for space missions, space robots have become the focus of research and attention. As a typical representative, the free-floating dual-arm space robot has the characteristics of multiple degrees of freedom, a floating base, and dynamic coupling between the manipulator and the base, so its modeling and control are very challenging. To address these challenges, a novel dynamic modeling and control method is proposed for a free-floating dual-arm space robot. First, an explicit dynamic model of a free-floating dual-arm space robot is established based on the explicit canonical multi-rigid-body dynamic modeling theory and combined with the concept of a dynamic equivalent manipulator. The establishment process of this model is not only simple and canonical to avoid the definition and calculation of many intermediate variables, but the symbolic result expression of the model also has the characteristics of iteration, which is convenient for computer automatic modeling. Next, aiming at addressing the problem of trajectory tracking and the base attitude stability of a free-floating dual-arm space robot with parameter perturbation and external disturbance, an improved nonlinear model predictive control method introducing the idea of sliding mode variable structure is proposed. Theoretical analysis shows that the proposed controller has better robustness than the traditional nonlinear model predictive controller. Then, an in-orbit service task is designed to verify the effectiveness of the proposed dynamic modeling and control strategy of the free-floating dual-arm space robot. Finally, the dynamic modeling and control methods proposed are discussed and summarized. The proposed methods can not only realize the tracking of the desired trajectory of the arms of the free-floating space robot, but can also realize the stable control of the base of the free-floating space robot. This paper provides new insights into the difficult problems regarding the dynamics and control of free-floating dual-arm space robots.

Attitude oscillation suppression control of a XK-I spherical robot

Purpose In complex environments, a spherical robot has great application value. When the pendulum spherical robot is stopped or disturbed, there will be a periodic oscillation. This situation will seriously affect the stability of the spherical robot. Therefore, this paper aims to propose a control method based on backstepping and disturbance observers for oscillation suppression. Design/methodology/approach This paper analyzes the mechanism of oscillation. The oscillation model of the spherical robot is constructed and the relationship between the oscillation and the internal structure of the sphere is analyzed. Based on the oscillation model, the authors design the oscillation suppression control of the spherical robot using the backstepping method. At the same time, a disturbance observer is added to suppress the disturbance. Findings It is found that the control system based on backstepping and disturbance observer is simple and efficient for nonlinear models. Compared with the PID controller commonly used in engineering, this control method has a better control effect. Practical implications The proposed method can provide a reliable and effective stability scheme for spherical robots. The problem of instability in real motion is solved. Originality/value In this paper, the oscillation model of a spherical robot is innovatively constructed. Second, a new backstepping control method combined with a disturbance observer for the spherical robot is proposed to suppress the oscillation.

Simultaneous identification of geometric parameters and structural stiffness of serial robots composing flexible links

It has been a formidable challenge to accurately predict the pose of serial robots composing flexible links due to the difficulties in simultaneously considering geometric errors and link flexibility. This paper presents an approach for simultaneously identifying kinematics and stiffness parameters in the flexible serial robot. A compliance equivalent method is employed to model the flexibility in the joints and links nonlinearly. Based on this, the kinetostatics model of those serial robots can be established analytically. By approximating the force-deflection characteristics of the flexible links, a unified error model containing both geometric and compliance parameters is derived. Moreover, an adaptive total-least-square method is proposed for the identification considering constraints on the compliance coefficient. To verify the effectiveness of the proposed method, simulations on a single flexible link, a serial robot, and experiments on a 3-DOF planar serial manipulator are carried out. The results show that the residual errors of the manipulator can be significantly reduced by identifying the kinematics and stiffness parameters using the proposed approach.

Tactile sensor-less fingertip contact detection and force estimation for stable grasping with an under-actuated hand

Detecting contact when fingers are approaching an object and estimating the magnitude of the force the fingers are exerting on the object after contact are important tasks for a multi-fingered robotic hand to stably grasp objects. However, for a linkage-based under-actuated robotic hand with a self-locking mechanism to realize stable grasping without using external sensors, such tasks are difficult to perform when only analyzing the robot model or only applying data-driven methods. Therefore, in this paper, a hybrid of previous approaches is used to find a solution for realizing stable grasping with an under-actuated hand. First, data from the internal sensors of a robotic hand are collected during its operation. Subsequently, using the robot model to analyze the collected data, the differences between the model and real data are explained. From the analysis, novel data-driven-based algorithms, which can overcome noted challenges to detect contact between a fingertip and the object and estimate the fingertip forces in real-time, are introduced. The proposed methods are finally used in a stable grasp controller to control a triple-fingered under-actuated robotic hand to perform stable grasping. The results of the experiments are analyzed to show that the proposed algorithms work well for this task and can be further developed to be used for other future dexterous manipulation tasks.

Simplified inverse dynamic models of parallel robots based on a Lagrangian approach

Simplified inverse dynamic models of parallel robots based on a Lagrangian approach

Design and Modeling of a Multi-DoF Magnetic Continuum Robot With Diverse Deformation Modes

Design and Modeling of a Multi-DoF Magnetic Continuum Robot With Diverse Deformation Modes

Error Modeling and Accuracy Analysis of Parallel Robots for Spacecraft Docking Motion Simulation System

Background: A large number of on-orbit docking dynamics experiments are conducted in the spacecraft docking motion simulation system with the development of Chinese space science and technology, and therefore, the requirement for high-precision parallel robots has increased. The pose accuracy of parallel robots is one of the most important problems in this application. Objective: In order to evaluate the pose accuracy of parallel robots in advance, a comprehensive pose accuracy analysis method considering major error sources is presented in this paper, and the influence of major error sources on the pose accuracy is also investigated to summarize the statistics and propagation characteristics of the pose error. Methods: The first-order error model for the parallel robot is established based on a generalized error model for each hydraulic cylinder and a sensitivity analysis method. Using the error model, a statistical approach to the parallel robot pose accuracy analysis is presented, and the influence of different parameter errors and different poses on the pose accuracy of the parallel robot is investigated. Sensitivity analysis is applied to evaluate the contribution of each parameter error to the position and orientation error of the parallel robot. An automated pose accuracy analysis program that computes and graphically displays the position and orientation error distributions and the sensitivity analysis results is developed. Results: The statistical analysis results of the influence of different parameter errors and different poses on pose accuracy are obtained by using the automated pose accuracy analysis program. The means of the position and orientation errors are close to zero. The standard deviations in the x and y directions are larger than those in the z direction, and these standard deviations are amplified with the increase of the parameter errors. For the given elevation, sensitivity analysis to various parameter errors is performed. It is found that the length error sensitivities of the hydraulic cylinders are less than one, and position error sensitivities of the hook joints A4, A5, and A6 are much greater than those of hook joints A1, A2 and A3. Conclusion: The elemental error sources belong to one of two groups, i.e., those affecting the hydraulic cylinder length and those affecting the hook joints. The distributions of the position and orientation errors are consistent with statistics theories. The parallel robot is more sensitive to the errors affecting the hook joints than those affecting the hydraulic cylinder length. These will help the designers and users of the parallel robot understand the statistics and propagation characteristics of the pose error. Some recent patents on error modeling and kinematic calibration of parallel robots are also discussed in this article.

Mathematical framework for snake robot motion in a confined space

Snake robots have redundant kinematic structure which predetermines them for motion in rough and unstructured terrain with obstacles, narrow spaces or environments with different ground levels. Dynamic modeling of snake robots is an important element in the development of control strategies for them. This paper, deals with the dynamic model of a snake robot moving in a pipeline. The model is based on Newton's mechanics with consideration of the viscous as well as Coulomb friction model. The paper uses Hertz theory for modeling of contact between a snake robot and side walls of a pipeline. Based on optimization process results, the friction effects as well as analyses of snake robot propulsive force are investigated. The main contributions of the paper are the developed dynamic model for snake robot motion in a pipeline, open source code of the developed model in MATLAB, and analyses of individual parameters of snake robot motion.

Model Predictive Control of Magnetic Helical Swimmers in Two-Dimensional Plane

Magnetic micro/mini-swimmers have a great potential application in biomedical research and have gained broad attention. Recent research studies focus on the automatic control methods of magnetic micro/mini-swimmers, such as artificial intelligence methods. However, their autonomous manipulation remains a challenge since they are subject to various disturbances from the external environment and model uncertainties. The current methods employ a status observer to estimate these disturbances and uncertainties. In this paper, we apply a data-driven technique that utilizes the nonlinear approximation ability of neural networks (NNs). To be specific, a flexible structure of NNs, Broad Learning System (BLS), is employed to model the input-output mapping relationship between the direction of the rotating magnetic field and the swimming direction of the helical miniature swimmer. Then, according to the dual-variable decoupling control, a levitation controller is formulated and a path following controller is proposed based on a planar three-degree-of-freedom model of magnetic helical swimmers, which is inspired by the model of wheeled mobile robots. Simulations and experiments are conducted to quantitatively validate the proposed control method using different planar paths. The experiment results show that the mean absolute error of the path following control is about 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula> of the body length which is less than 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$mm$</tex-math> </inline-formula> . Our proposed control method provides a preliminary study to alleviate the impact of disturbances and uncertainties on the control performance of magnetic micro/mini-swimmers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is mainly motivated by the potential application of artificial intelligence methods in magnetic micro/mini-robot community, especially for the applications that reject disturbances and uncertainties. In practice, a path planner is employed to compute a pre-defined reference path that connects the start and the targeted locations. Then our control method is applied to the magnetic helical swimmer and it is guided to follow the reference path. Tackling external disturbances and model uncertainties is still challenging during the control progress. Neural network-based technique is an intuitive approach since their nonlinear modeling ability and generalization are suitable for estimating these disturbances and uncertainties. As for training the neural-network model, the training data about the angle parameters should be recorded by manual control of the helical swimmer. These angle parameters define the rotating axis of the uniform rotating magnetic field and the self-rotating axis of the magnetic helical swimmer. According to the planar motion model, the optimal controller is formulated using the feedback distance error and angle error, and the sum of the control signal and the prediction of the compensating model is used as the final control input. Our electromagnetic coil system features easy operation and configuration of cameras or other sensors. Simulations and experiments validate the performance of the neural network-based compensating method and the proposed optimal control method using magnetic micro/mini-swimmers.

Kinematics-Informed Neural Networks: Enhancing Generalization Performance of Soft Robot Model Identification

Kinematics-Informed Neural Networks: Enhancing Generalization Performance of Soft Robot Model Identification

Development of Portable Magnetic Adsorption Amphibious Robot

In this study, a portable magnetic adsorption amphibious robot which can operate on and below the waterline is developed for special curved environments, such as the pile legs of offshore platforms and the outer walls of ships. An open robot integrated control system based on a domestic chip is developed, and two operating modes of local control operation and remote wireless operation are realized. A permanent magnet adsorption scheme combining a magnetic adsorption track and a synchronous belt wheel is designed, static and dynamic analysis of the wall-climbing operation of the robot is carried out, and a kinematic model of the underwater robot is established. The experimental results show that the robot can effectively complete amphibious tasks and can realize the accurate control of attitude in water, proving it to be an effective tool for amphibious tasks, such as operating on the pile legs of offshore platforms and the outer walls of ships.

Predefined-time distributed optimization and anti-disturbance control for nonlinear multi-agent system with neural network estimator: A hierarchical framework

This paper addresses the predefined-time distributed optimization of nonlinear multi-agent system using a hierarchical control approach. Considering unknown nonlinear functions and external disturbances, we propose a two-layer hierarchical control framework. At the first layer, a predefined-time distributed estimator is employed to produce optimal consensus trajectories. At the second layer, a neural-network-based predefined-time disturbance observer is introduced to estimate the disturbance, with neural networks used to approximate the unknown nonlinear functions. A neural-network-based anti-disturbance sliding mode control mechanism is presented to ensure that the system trajectories can track the optimal trajectories within a predefined time. The feasibility of this hierarchical control framework is verified by utilizing the Lyapunov method. Numerical simulations are conducted separately using models of robotic arms and mobile robots to validate the effectiveness of the proposed method.

Posture Optimization of the TIAGo Highly-Redundant Robot for Grasping Operation

This study explores the optimization of the TIAGo robot’s configuration for grasping operation, with a focus on the context of aging. In fact, featuring a mobile base and a robotic arm, the TIAGo robot can conveniently aid individuals with disabilities, including those with motor and cognitive impairments in both domestic and clinical settings. Its capabilities include recognizing visual targets such as faces or gestures using stereo cameras, as well as interpreting vocal commands through acoustic sensors to execute tasks. For example, the robot can grasp and lift objects such as a glass of water and navigate autonomously in order to fulfill a request. The paper presents the position and differential kinematics that form the basis for using the robot in numerous application contexts. In the present case, they are used to evaluate the kinematic performance of the robot relative to an assigned pose in the search for the optimal configuration with respect to the higher-order infinite possible configurations. Ultimately, the article provides insight into how to effectively use the robot in gripping operations, as well as presenting kinematic models of the TIAGo robot.

Dynamic tail modeling and motion analysis of a beaver-like robot

Dynamic tail modeling and motion analysis of a beaver-like robot

Kinematic modeling and simultaneous calibration for acupuncture robot

Acupuncture robot is a new-era product combining traditional acupuncture and cutting-edge technology. The calibration of the vision system and the acupuncture mechanism is a crucial prerequisite for humanoid acupuncture control, which has not yet been explored. In this paper, a simultaneous offline calibration method is proposed for acupuncture robots. Analysis reveals that its calibration problem is defined with three closed kinematic chains, while the typical problems cover only a single chain. Decoupling them, a Kronecker product-based method is deduced to access the closed-form rotation component. As opposed to quaternion-based methods, it only experiences linear complexity in sign ambiguity, which can produce a more precise solution in finite time. Further, a simultaneous optimization model that encompasses all components is established, which can be solved with stochastic gradient descent-based methods. It is free of truncation errors and thus has higher calibration accuracy and convergence speed. Besides, the impairment in error propagation between different closed kinematic chains is mitigated compared to step-by-step methods. Finally, simulations and experiments are carried out. Notably, the proposed method can be easily extended to other robot calibration problems with multiple closed kinematic chains.

Advancing Legged Wall Climbing Robot Performance Through Dynamic Contact-Integrated Climbing Model

Abstract Climbing robots have gained significance in hazardous and steep terrains, yet adapting to complex environments remains a challenge. Inspired by nature's climbers, this paper introduces a climbing dynamics model that integrates foot-end contact forces, crucial for safe and efficient wall climbing. Drawing insights from animal locomotion and biomechanics, we present a comprehensive dynamic model for quadruped robots. Our model, built upon multibody dynamics and a dynamic contact model based on spiny claw mechanisms, accurately simulates robot forces and motion during climbing, even predicting failure scenarios. Experimental validation further establishes model accuracy. This study advances climbing robot research by addressing attachment interaction dynamics and provides valuable insights for optimizing robot structural design and gait strategies.

Development of a novel nonlinear model and control strategy for soft continuum robots featuring hard magnetoactive elastomers

Magnetoactive soft continuum robots (MSCRs), capable of controllable steering and navigation, hold substantial promise for healthcare applications. However, advancements in MSCRs have been hindered by a limited understanding of MSCR dynamics and a lack of effective control methods. Addressing these gaps, this study presents a novel, time-dependent, and computationally efficient analytical model of MSCR, alongside a new optimal closed-loop control strategy for precise high-frequency trajectory tracking. A finite element (FE) model of the MSCR is initially developed, with its validity confirmed through rigorous laboratory measurements. Using the formulated FE model, a new and computationally efficient analytical model is subsequently developed to accurately predict the highly nonlinear response of MSCR. This model operates as a system of switched linear models, each of which is a reduced-order version of its corresponding high-order linear model extracted from the FE analysis. This innovative approach not only maintains the predictive accuracy of the FE model but also significantly reduces computational demands, operating in just a few seconds. The results highlight that the developed model can accurately predict the dynamic responses of the MSCR while significantly reducing the computational load by almost 80 orders of magnitude compared with the FE model on the same simulation platform. The proposed model has been effectively utilized to develop a novel optimal control strategy using the feedforward interval type-2 fractional-order fuzzy-PID method. A hardware-in-the-loop experimental test has been finally designed to demonstrate the superior performance of the MSCR under the proposed controller.

Effects of Fibular Plate Fixation on Ankle Stability in a Weber B Fracture Model With Partial Deltoid Ligament Sectioning.

Weber B fractures with concomitant deltoid ligament injury have traditionally been operated with open reduction and internal fixation of the fibular fracture. More recently, clinical studies have suggested that some fractures have concomitant partial deltoid ligament injury with the deep posterior tibiotalar ligament intact (SER4a), allowing for nonoperative treatment in this subgroup. This study explores whether plate fixation of the fibula improves ankle stability in an SER4a injury model. And if so, does it restore native ankle stability? Fifteen cadaver ankle specimens were tested in 3 states using an industrial robot: intact joint, SER4a models without plate fixation of the fibula, and SER4a models with plate fixation of the fibula. The robot measured ankle stability in lateral translation, valgus, and internal and external rotation in 3 talocrural joint positions: 10 degrees dorsiflexion, neutral, and 20 degrees plantar flexion. Furthermore, fluoroscopic mortise view radiographs were taken to measure isolated talar shift and talar tilt. The talar shift and tilt tests showed no differences between the SER4a injury model with and without fibular plate fixation at neutral ankle position with a mean difference of -0.16 mm (95% CI -0.33 to 0.01 mm, P = .071) for talar shift and -0.15 degrees (95% CI -0.01 to 0.30 degrees, P = .068) for talar tilt. However, plate fixation increased external rotation stability, with mean improvements ranging from -7.43 to -9.52 degrees (P < .001 for all comparisons), but did not restore intact ankle stability. For internal rotation, plate fixation resulted in minor differences. The results of this suggest that plate fixation of the fibular fracture primarily improves external rotation stability but does not substantially improve lateral translation, valgus, or internal rotation stability in SER4a injury models. In this robotic cadaver model, fibular plate fixation did not fully restore intact ankle stability after simulated SER4a injury. This study offers insights into the effects of fibular plate fixation on Weber B/SER4a injury models and may assist informed decisions when selecting treatments for these types of fractures.

Search for Optimal Parameters in the Control Structure of a Surgical System for Soft Tissue Operations Based on In Vitro Experiments on Cardiovascular Tissue

The surgical robots currently used in cardiac surgery are equipped with a remote center of motion (RCM) mechanism that enables the required spherical workspace. The dynamics model of the surgical robot’s RCM mechanism presented in this work includes a direct current (DC) motor, an optimal proportional–integral–derivative (PID) controller, and a LuGre friction model that takes into account the Stribeck effect and surface deformation. A finite element method (FEM) analysis of transients was carried out using the energy hypothesis of von Mises with an optimal input signal from the mechatronic system with a PID controller obtained using the Runge–Kutta differentiation method in the Dormand–Prince ordinary differential equations variant (ODE45). Five criteria were adopted for the objective function: the safety factor related to the stress function in the time-varying strength problem, the first natural frequency related to stiffness and the resonance phenomenon, the buckling coefficient in the statics problem related to stability, the static factor of safety, and the displacement of the operating tip. The force inputs to the dynamics model were derived from in vitro force measurements on cardiovascular tissue using a force sensor. The normality of the statistical distribution of the experimental data was confirmed using the Kolmogorov–Smirnov statistical test. The problem of multi-criteria optimization was solved using the non-sorter genetic algorithm (NSGA-II), the finite element method, and the von Mises distortion energy hypothesis. Velocity input signals for the transient dynamics model were obtained from a second in vitro experiment on cardiovascular tissue using the minimally robotic invasive surgery (MIRS) technique. An experienced cardiac surgeon conducted the experiment in a modern method using the Robin Heart Vision surgical robot, and a system of four complementary metal–oxide–semiconductor (CMOS) optical sensors and ariel performance analysis system (APAS-XP 2002) software were used to obtain the endoscopic tool trajectory signal. The trajectory signal was accurate to ±2 [mm] in relation to the adopted standard, and it was smoothed using the Savitzky–Golay (SG) polynomial smoothing, whose parameters were optimally selected using the Durbin–Watson (DW) statistical test.