Circular Trajectory Tracking Research Articles

Development of a Minimally Invasive Surgical Robot Using Self-Helix Twisted Artificial Muscles

In the field of surgery, minimally invasive surgical robots (MISRs) have emerged as the persistent pursuit of physicians to minimize harm and perform precise surgery. The structure of newly proposed MISRs tends to change form rigid to flexible, which poses a challenge to precise control. In this work, a MISR actuated by self-helix twisted artificial muscles (SHTAMs) with large bending angle and high precision is developed. The configuration and operation principle of the MISR are illustrated. Then, the physical model of SHTAM and the kinematics model of the end effector are established. The contraction ratio of SHTAM reaches 27.5%, and the output force is 5424.2 mN. Besides, the maximum bending angle (about 92°) of MISR is measured to verify the kinematic analysis. Moreover, in the point positioning control experiments, the steady-state error is less than 0.11°. Subsequently, the trajectory tracking tests on sinusoidal trajectories with different frequencies and amplitudes are carried out, and the circular trajectory tracking experiment is also performed with a maximum error of 1.8° in cold gel environment. The experimental results indicate that the proposed MISR has a large bending angle and can achieve accurate trajectory control, which exhibits excellent prospect in precision minimally invasive surgery.

A modular continuous robot constructed by Miura-derived origami tubes

Folding a flat sheet under a specific crease pattern can form a three-dimensional origami tube, which has been proven to exhibit unique mechanical properties and has wide engineering applications. In this study, a novel Miura-derived origami tube is designed, and its precise circular closing condition and mechanical properties are systematically analyzed, revealing that the proposed origami tube has programmable stiffness characteristics. Polyvinyl chloride (PVC) sheet enables the origami tube to have the characteristics of flexibility, bending, compression, and torsion resistance. Then, a modular design strategy for the novel continuous robot constructed with the Miura-derived origami tube as the backbone is proposed. A continuous robot with three origami tube modules in series is designed and fabricated as a representative case. Three steel wires drive each module to achieve independent contraction or bending movement. The unified installation of steel wire-driven motors on the base endows the robot with a lightweight, interconnected inner space, high scalability, and flexibility backbone. The kinematic relationships among the driving space, configuration space, and task space are investigated by geometric model and constant curvature assumption, with the circular trajectory tracking and reachable workspace revealed by numerical simulations. Further, the kinematic decoupling or the multi-driving model based on the stiffness difference of the origami tube between multi-segments is discussed. Finally, three prototype experiments demonstrate both the rationality of introducing origami tubes to design the continuous robot and the application potential.

Development of a three-degree-of-freedom piezoelectric actuator.

Multi-degree of freedom piezoelectric actuators are strongly needed for industrial applications, especially when manipulating a large and heavy mirror or lens in an optical system. A novel three-degree-of-freedom piezoelectric actuator, which is driven by two pairs of piezo-stack actuator with spatial compliant mechanisms designed to guide the motion and preload the piezo-stack actuators, is herein proposed. The structure and working principle of the proposed actuator are illustrated and its kinematic characteristic is analyzed. The stiffness of the spatial compliant mechanisms is modeled, and the dynamic characteristics are analyzed, Finite Element method is utilized to validate the correctness of the stiffness modeling and the free vibration analysis of the proposed actuator. A prototype actuator is fabricated and its output performances have been tested. Working space of X ranging from -7.1 to 5.6μm, Y ranging from -6.2 to 8.2μm and Z ranging from -2.3 to 2.1μm, displacement resolutions of 15/16/21nm along X-/Y-/Z-axis and average velocities of 52.3, 82.8 and 29.5 µm/s along X-axis, Y-axis, and Z-axis with carrying load up to 2kg and driving frequency of 500Hz have been achieved by the prototype actuator. The method of waveform generating for the proposed actuator has been developed with the inverse hysteresis compensation, and test results indicate that the positioning accuracy of the prototype actuator in the open loop has been improved from 0.94 to 0.23μm for a circular trajectory tracking, from 0.48 to 0.29 μmm for an elliptical trajectory tracking, and from 0.61 to 0.32μm for a rectangular trajectory tracking with the compensated waveform of driving voltage.

Model predictive control using LPV approach for trajectory tracking of quadrotor UAV with external disturbances

PurposeThe rotorcraft technology is very interesting area since last few decades due to variety of applications. One of the rotorcrafts is the quadrotor unmanned aerial vehicle (QUAV), which contains four rotors mounted on an airframe with an onboard controller. The QUAV is a highly nonlinear system and underactuated. Its controller design is very challenging task, and the need of controller is to make it autonomous based on mission planning. The purpose of this study is to design a controller for quadrotor UAV for attitude stabilization and trajectory tracking problem in presence of external environmental disturbances such as wind gust.Design/methodology/approachTo address this problem, the model predictive control has been designed for attitude control and feedback linearization control for the position control using the linear parameter varying (LPV) approach. The trajectory tracking problem has been addressed using the circular trajectory and helical trajectory.FindingsThe simulation results show the efficient performance with good trajectory tracking even in presence of external disturbances in both the scenarios considered, one for circular trajectory tracking and other for helical trajectory tracking.Originality/valueThe novelty of the work came from using the LPV approach in controller design, which increases the robustness of the controller in presence of external disturbances.

Finite-time tracking control for nonholonomic wheeled mobile robot using adaptive fast nonsingular terminal sliding mode

System uncertainties and external disturbances are the major causes of the trajectory tracking performance degradation in nonholonomic wheeled mobile robots (NWMRs). In this article, an adaptive fast nonsingular terminal sliding mode dynamic control (AFNTSMDC) method is proposed to provide enhanced robust and finite-time tracking performance for the NWMR. The proposed AFNTSMDC is a systematic design method based upon both the kinematic and dynamic model of the NWMR. The proposed controller has a simple form without singularity issue in the control input, which makes it practically implementable. The finite-time stability of the proposed tracking-error function is also proved using the Lyapunov function. Finally, circular trajectory tracking experiments are conducted to validate the robustness and convergence rate of the proposed AFNTSMDC scheme in comparison with the existing methods including classic kinematic control, robust sliding mode kinematic control, and conventional sliding mode dynamic control in the presence of uncertainties and external disturbances.

Bionic fish tail design and trajectory tracking control

Bionic fish have received wide attention due to their high mobility, high concealment, and high propulsion efficiency. This paper proposes a new type of bionic fish tail, uses the fish body wave equation and penalty function to optimise its parameters, and then conducts a multimodal motion simulation using Adams to verify the feasibility of the bionic fish tail. Second, to realise the trajectory tracking control of the bionic fish, the central pattern generator (CPG) and the sliding mode controller are combined through the transfer function obtained by experiments and data fitting, and a CPG-based sliding mode controller (SMC-CPG Controller) is proposed and proven to be stable. Finally, simulations and experiments of bionic fish tracking under straight and circular trajectories are performed. The experiments show that under the initial error conditions, the bionic fish can quickly eliminate the position error and the heading angle error under the control of the SMC-CPG controller and track the expected trajectory. The position errors for straight and circular trajectory tracking are 8.62% and 11.5% of the body length, respectively, and the heading angle error during the movement always fluctuates between −40° and 60°. The effectiveness of the proposed SMC-CPG controller and the bionic fish tail is verified through experiments.

A robust control design approach for altitude control and trajectory tracking of a quadrotor

Introduction. Unmanned aerial vehicles as quadcopters, twin rotors, fixed-wing crafts, and helicopters are being used in many applications these days. Control approaches applied on the quadrotor after decoupling the model or separate altitude control and trajectory tracking have been reported in the literature. A robust linear H∞ controller has been designed for both altitude control and circular trajectory tracking at the desired altitude. Problem. The ability of the quadrotor system to hover at a certain height and track any desired trajectory makes their use in many industrial applications in both military and civil applications. Once a controller has been designed, it may not be able to maintain the desired performance in practical scenarios, i.e. in presence of wind gusts. Originality. This work presents the control strategy to ensure both altitude control and trajectory tracking using a single controller. Purpose. However, there is a need for a single controller that ensures both altitude control and trajectory tracking. Novelty. This paper presents a robust H∞ control for altitude control and trajectory tracking for a six degree of freedom of unmanned aerial vehicles quadrotor. Methodology. Multi input multi output robust H∞ controller has been proposed for the quadrotor for altitude control and tracking the desired reference. For the controller validation, a simulation environment is developed in which a 3D trajectory is tracked by the proposed control methodology. Results. Simulation results depict that the controller is efficient enough to achieve the desired objective at minimal control efforts. Practical value. To verify that the proposed approach is able to ensure stability, altitude control, and trajectory tracking under practical situations, the performance of the proposed control is tested in presence of wind gusts. The ability of the controller to cater to the disturbances within fractions of seconds and maintaining both transient and steady-state performance proves the effectiveness of the controller.

Tracking Control of Pneumatic Artificial Muscle-Activated Robot Arm Based on Sliding-Mode Control

This study discusses a circular trajectory tracking function through a proposed pneumatic artificial muscle (PAM)-actuated robot manipulator. First, a dynamic model between a robot arm and a PAM cylinder is introduced. Then the parameters thereof are identified through a genetic algorithm (GA). Finally, PID is used along with a high-order sliding-mode feedback controller to perform circular trajectory tracking. As the experimental results show, the parameters of sampling time and moment of inertia are set to accomplish the trajectory tracking task in this study. In addition, the maximum error between the objective locus and the following locus was 11.3035 mm when applying theta-axis control to the circular trajectory of the robot arm with zero load or lower load. In an experiment of controller comparison, the results demonstrate that a high-order sliding-mode feedback controller is more robust in resisting external interference and the uncertainty of modeling, making the robot arm have good performance when tracking.

A Tilting-Rotor Unmanned Aerial Vehicle for Enhanced Aerial Locomotion and Manipulation Capabilities: Design, Control, and Applications

In this article, a novel multirotor unmanned aerial vehicle (UAV) is proposed for enhanced locomotion and manipulation in unstructured environments. The vehicle has a tilting-rotor architecture. Specifically, two pairs of rotors are mounted on two independently controlled tilting arms placed at two sides of the vehicle, forming an “H” configuration. Such a structure endows the vehicle with more degrees of freedom, improving the maneuverability without sacrificing energy efficiency at the cost of only two additional servos compared to traditional quadcopters. Based on this architecture, a dual-level adaptive robust control is developed to cope with inertial parametric uncertainties and uncertain nonlinearities for accurate motion tracking. To resolve the redundancy in actuation, a thrust force optimization problem minimizing power consumption while achieving the desired body force wrench is formulated and solved precisely and efficiently. With the novel design and control, the proposed aerial vehicle is capable of achieving superior maneuverability, better stability and motion accuracy in the presence of uncertainties, as well as improved power efficiency compared to traditional UAVs when performing dexterous aerial locomotion and manipulation. To demonstrate the advantage of the proposed new UAV design and control in real applications, we conduct four challenging experiments on aerial locomotion and manipulation: circular trajectory tracking, passing through a narrow tunnel, picking up an object from a cluttered shelf, and aerial hole drilling. Experimental results validate the applicability of the proposed innovation.

Motion modeling of a non-holonomic wheeled mobile robot based on trajectory tracking control

Trajectory tracking is a problem of emphasis for the mobile robot. In this study, a coordinate transformation method was used to build a kinematic model of the wheeled mobile robot. A traditional proportional-integral-derivative control method was researched and improved by combining it with a neural network. A neural network proportional-integral-derivative trajectory tracking control method was thus designed, and a simulation experiment was performed using Simulink. The results show that in circular trajectory tracking control, the maximum errors of the X axis, Y axis, and θ were approximately 2.1 m, 2.3 m, and 0.4 rad, respectively, and that the system remained stable after running for 10 s. In straight-line trajectory tracking control, the maximum errors of the X axis, Y axis, and θ were approximately −0.8 m, 1.3 m, and 0.3 rad, respectively, and the system remained stable after running for 8 s. The error was relatively small, and the effect of trajectory tracking control was good. The studied method had good performance in terms of wheeled mobile robot trajectory tracking control and is worthy of further promotion and application.

A Segmented Geometry Method for Kinematics and Configuration Planning of Spatial Hyper-Redundant Manipulators

With many degrees of freedom (DOFs), a hyper-redundant manipulator has superior dexterity and flexible manipulation ability. However, its inverse kinematics and configuration planning are very challenging. With the increase in the number of DOFs, the corresponding computation load or training set will be much larger for traditional methods (such as the generalized inverse method and the artificial neural network method). In this paper, a segmented geometry method is proposed for a spatial hyper-redundant manipulator to solve the above problems. Similar to the human arm, the hyper-redundant manipulator is segmented into three sections from geometry, i.e., shoulder, elbow, and wrist. Then, its kinematics can be solved separately according to the segmentation, which reduces the complexity of the solution and simplifies the computation of the inverse kinematics. Furthermore, the configuration is parameterized by several parameters, i.e., the arm-angle, space arc parameters, and desired direction vector. The shoulder has proximal four DOFs, which is redundant for positioning the elbow and avoiding the joint limit. The arm-angle parameter is defined to solve the redundancy. The wrist consists of the distal two DOFs, and its joints are determined to match the desired direction vector of the end-effector. All the other joints (except for the joints belonging to shoulder and wrist) compose the elbow. These joint angles are solved by using space arc-based method. The configuration planning for avoiding joint limit, obstacles, and inspecting narrow pipeline are detailed for practical applications. Finally, circular trajectory tracking and pipeline inspection are, respectively, simulated and experimented on a 20-DOFs hyper-redundant manipulator. The results show that the proposed method can give solutions of the three-dimensional-pose-determining problem and the configuration-planning problem. The computation of the inverse kinematics is simplified for real-time control. It can also be applied to other spatial hyper-redundant manipulators with similar serial configurations.

Research on Tracking Control of Circular Trajectory of Robot Based on the Variable Integral Sliding Mode PD Control Algorithm

An algorithm named Variable Integral Sliding Mode PD Control (VISMPDC) which combines integral sliding mode control with the PD control method is proposed to improve the trajectory tracking control accuracy and robustness of a robot along the representative circular trajectory. According to the difference of the time weighting coefficients in the time-jerk optimal objective function (when the time weighting coefficient increases from 0 to 1, the movement velocity of a robot changes from low to high), the obtained optimization trajectories are divided into two categories: low-speed and high-speed; and then the integral sliding mode control parameters are adjusted, while the parameters of the PD control method keep unchanged. The experimental results on a 7-DOF robot show that the proposed algorithm is effective and feasible when compared with the traditional PD control method. In conclusion, the algorithm presents a solution for the typical circular trajectory tracking control problem of a robot.

Model Identification and Trajectory Tracking Control for Vector Propulsion Unmanned Surface Vehicles

To promote the development of military and civilian applications for marine technology, more and more scientific research around the world has begun to develop unmanned surface vehicles (USVs) technology with advanced control capabilities. This paper establishes and identifies the model of vector propulsion USV, which is widely used at present. After analyzing its actuator distribution, we consider that the more realistic vessel model should be an incomplete underactuated system. For this system, a virtual control point method is adopted and an adaptive sliding mode trajectory tracking controller with neural network minimum learning parameter (NNMLP) theory is designed. Finally, in the simulation experiment, the thruster speed and propulsion angle are used as the inputs of the controller, and the linear and circular trajectory tracking tests are carried out considering the delay effect of the actuator, system uncertainty, and external disturbance. The results show that the proposed tracking control framework is reasonable.

Adaptive Trajectory Tracking of Wheeled Mobile Robots Based on a Fish-eye Camera

This paper presents a novel adaptive trajectory tracking control method, which can precisely control wheeled mobile robots only using an uncalibrated fish-eye camera fixed on the ceiling. Different from existing approaches, the inertial device, distorted image correction, and the trajectory expression are not required in the control system. The position and orientation of the mobile robot in the camera coordinate system are estimated by the extended POSIT (Pose from Orthography and Scaling with Iteration) algorithm in real-time. Based on estimation results, the controller considering both tracking errors and parameter estimated errors is designed by linear parameterization, where the camera intrinsic parameters are online updated. The asymptotic convergence of the tracking error and the estimated error to zero is proved by the Barbalat lemma. Circular trajectory and irregular trajectory tracking experiments have been conducted to verify the performance of our controller.

Adaptive Admittance Control of an Upper Extremity Rehabilitation Robot With Neural-Network-Based Disturbance Observer

Robot-assisted rehabilitation therapy has become an important technology applied to recover the motor functions of disabled individuals. In the present paper, an adaptive admittance control strategy combined with a neural-network-based disturbance observer (AACNDO) is developed for a therapeutic robot to provide upper extremity movement assistance. Firstly, a comprehensive overview of the robot hardware and real-time control system is introduced. Then, the dynamics-based adaptive admittance controller is designed to improve human-robot interaction compliance and induce the active participation of the patients during rehabilitation training. A disturbance observer with a radial basis function network is designed to guarantee the control performance with external uncertainties and dynamics error. Besides, an adaption law is integrated into the admittance model to adjust the interaction compliance in different working areas based on the motion intention and recovery phase of the patient. Further experimental investigations, including sinusoidal trajectory tracking experiments, circular trajectory tracking experiments with admittance adjustment, and intention-based resistive training experiments, are conducted by three volunteers. Finally, the experimental results validate the feasibility and effectiveness of the rehabilitation robot and AACNDO scheme in providing patient-passive and patient-cooperative rehabilitation training.

Research on AGV trajectory tracking control based on double closed-loop and PID control

Aimed at AGV motion model of two-wheeled differential drive control mode, AGV motion control is divided into double closed-loop trajectory tracking control based on Lyapunov direct method and sliding-mode control technology and speed control based on PID method through hierarchical control thought. Double closed-loop control technology researches trajectory tracking control problem of AGV under Cartesian coordinate system; PID control method researches real-time speed control problem of drive motor of AGV. Finally, circular trajectory tracking simulation test is made to AGV under Matlab/Simulink environment. Simulation result shows that system has correct positioning with fast dynamic response and good robustness, and verifies feasibility and effectiveness of scheme proposed.

Quaternion based control for circular UAV trajectory tracking, following a ground vehicle: Real-time validation

This work proposes a quaternion-based circular trajectory tracking control scheme, in which an Unmanned Aerial Vehicle (UAV) follows an Unmanned Ground Vehicle (UGV). A trajectory is generated, including a switching technique for takeoff, positioning, and landing stages, such that the UAV describes circles over the UGV using equilibrium point bifurcations. This technique could be applied in missions where a perimeter must be inspected by heterogeneous robots, the UAV can be deployed from the UGV’s location, such that its perimeter is visualized from above. Our proposal is validated usig numerical simulations and real-time experiments.

Design and Implementation of Classical Sliding Mode Controller for Ball and Plate System

Ball and Plate (B&P) system is a benchmark system in the control engineering field that has been used to verify many control methods. In this paper the design of a sliding mode . controller has been investigated and verified in real-time via implementation on a real ball and plate system hardware. The mathematical model has been derived and the necessary parameters have been measured. The sliding mode controller has been designed based on the obtained mathematical model. The resulting controller has been implemented using the Arduino Mega 2560 and a ball and plate system built completely from scratch. The Arduino has been programmed by the Arduino support target for Simulink. Three test signals has been used for verification purposes, namely: single point stabilizing, circular trajectory tracking, and square trajectory tracking. The results obtained have shown that sliding mode controller is able to follow the desired test signals with low error.

Multi-constrained model predictive control for autonomous ground vehicle trajectory tracking

A multi-constrained model predictive control (MPC) algorithm for trajectory tracking of an autonomous ground vehicle is proposed and tested in this paper. First, to simplify the computation, an active steering linear error model is applied in the MPC controller. Then, a control increment constraint and a relaxing factor are taken into account in the objective function to ensure the smoothness of the trajectory, using a softening constraints technique. In addition, the controller can obtain optimal control sequences which satisfy both the actual kinematic constraints and the actuator constraints. The circular trajectory tracking performance of the proposed method is compared with that of another MPC controller. To verify the trajectory tracking capabilities of the designed controller at different desired speed, the simulation experiments are carried out at the speed of 3m/s, 5m/s and 10m/s. The results demonstrate the MPC controller has a good speed adaptability.

Neural Network Control for Position Tracking of a Two-Axis Inverted Pendulum System: Experimental Studies

In this paper, experimental studies of a decentralized neural network control scheme of the reference compensation technique applied to control a 2-degrees-of-freedom (2-DOF) inverted pendulum on an x - y plane are presented. Each axis is controlled by two separate neural network controllers to have a decoupled control structure. Neural network controllers are applied not only to balance the angle of pendulum, but also to control the position tracking of the cart. The decoupled control structure can compensate for uncertainties and cancel coupling effects. Especially, a circular trajectory tracking task is tested for position tracking control of the cart while maintaining the angle of the pendulum. Experimental result shows that position control of the inverted pendulum and cart is successful.