In this paper, based on the Youla-Kucera (Y-K) parameterization, the control of a flexible beam acting as a flexible robotic manipulator is investigated. The method of Youla parameterization is the simple solution and proper method for describing the collection of all controllers that stabilize the closed-loop system. This collection comprises function of the Youla parameter which can be any proper transfer function that is stable. The main challenge in this approach is to obtain a Youla parameter with infinite dimension. This parameter is approximated by a subspace with finite dimensions, which makes the problem tractable. It is required to be generated from a finite number of bases within that space and the considered system can be approximated by an expansion of the orthonormal bases such as FIR, Laguerre, Kautz and generalized bases. To calculate the coefficients for each basis, it is necessary to define the problem in the form of an optimization problem that is solved by optimization techniques. The Linear Quadratic Regulator (LQR) optimization tool is employed in order to optimize the controller gains. The main aim in controller design is to merge the closed-loop system and the second order system with the desirable time response characteristic. The results of the Youla stabilizing controller for a planar flexible manipulator with lumped tip mass indicate that the proposed method is very efficient and robust for the time-continuous instances.

This paper presents a systematic approach to compute the angularity and the axiality indices for a Schönflies parallel manipulator. Angularity index may be considered as a measure of the sensitivity of the mobile platform to changes in rotation, while axiality index can be used to measure the sensitivity of the OP of the mobile platform to changes in translation. Since both indices were inspired by very fundamental concepts of classical kinematics (angular velocity vector and helicoidal velocity field), they offer a clear and simple physical meaning, which may be useful to the designer of parallel manipulators. Moreover, both dexterity indices do not require obtaining a dimensionally homogeneous Jacobian matrix, nor do they depend on having similar types of actuators in each manipulator's leg. Detailed numerical examples are given in order to illustrate the computation of the dexterity indices.

It is well known that the use of multi-rate control techniques have improved the performance of many systems in general, and robotic systems, in particular. The main contribution of this paper is the generalization of the Reference Filtering control strategy from a dual-rate point of view, improving its inherent properties by overcoming the problem of sensor latency. In the paper, we discuss and analyze the improvements introduced by the novel dual-rate reference filtering control strategy in terms of convergence time, reachability and robustness. More specifically, we discuss the capability to solve positioning tasks, when hardware limitations are present with large sampling rates. In addition, a comparison is made between the single-rate and the proposed dual-rate control strategies to prove the advantages of the latter approach. A complete set-up has been prepared for validation, including a six degree of freedom (DOF) industrial manipulator, a smart camera and embedded hardware used as a high level controller.

The determination of the assembly modes of the parallel structures with three legs of type PS or SP (P and S stand for prismatic pair and spherical pair, respectively) consists of solving the direct position analysis of all the three-legged parallel manipulators which have, in each leg, one not actuated prismatic pair, one not actuated spherical pair and one or two one-dof actuated pairs of any type, placed along the leg in any order. There are two types of such structures: (i) 3PS structures and (ii) SP-2PS structures. The procedure to determine the assembly modes of the SP-2PS structures has not been presented yet, in the literature. This paper presents the analytic form determination of the assembly modes of the SP-2PS structures. In particular, the closure equations of a generic SP-2PS structure will be written and their solution will be reduced to the solution of an eight-degree univariate polynomial equation with real coefficients. Finally, the proposed algorithm will be applied to a real case. The result of this study is that the assembly modes of any SP-2PS structure are at most eight, and the end-effector poses, which solve the direct position analysis of the parallel manipulators that generate those structures, are also eight.

We present a control method for a simple limit-cycle bipedal walker that uses adaptive frequency oscillators (AFOs) to generate stable gaits. Existence of stable limit cycles is demonstrated with an inverted-pendulum model. This model predicts a proportional relationship between hip torque amplitude and stride frequency. The closed-loop walking control incorporates adaptive Fourier analysis to generate a uniform oscillator phase. Gait solutions (fixed points) are predicted via linearization of the walker model, and employed as initial conditions to generate exact solutions via simulation. Global stability is determined via a recursive algorithm that generates the approximate basin of attraction of a fixed point. We also present an initial study on the implementation of AFO-based control on a bipedal walker with realistic mass distribution and articulated knee joints.

This paper proposed an elastodynamic modeling method combined with independent displacement coordinates and substructure synthesis technology. Firstly, the connecting rod was discretized, and the elastodynamic control equation for each element was established. The multipoint constraint element theory, linear algebra, and singularity analysis were used to identify the globally independent displacement coordinates of the manipulator. On this basis, the elastodynamic model using the substructure synthesis for the 3-PRS parallel manipulator (PM) was developed, with its natural frequencies distribution in the regular workspace discussed. The comparison with the finite-element results showed that the maximum error of the first three-order natural frequencies was within 1.03%, which verified the correctness of the analytical model. The proposed elastodynamic model included all the kinematic constraints of the manipulator without increasing the Lagrangian multiplier. The method is computationally efficient and assesses the dynamic behaviors of the mechanism at the predesign phase.

Clinical observations and subjective judgements have traditionally been used to evaluate patients with muscular and neurological disorders. As a result, identifying and analyzing functional improvements are difficult, especially in the absence of expertise. Quantitative assessment, which serves as the motivation for this study, is an essential prerequisite to forecast the task of the rehabilitation device in order to develop rehabilitation training. This work provides a quantitative assessment tool for muscle weakness in the human upper limbs for robotic-assisted rehabilitation. The goal is to map the assessment metrics to the recommended rehabilitation exercises. Measurable interaction forces and muscle correlation factors are the selected parameters to design a framework for muscular nerve cell condition detection and appropriate limb trajectory selection. In this work, a data collection setup is intended for extracting muscle intervention and assessment using MyoMeter, Goniometer and surface electromyography data for upper limbs. Force signals and human physiological response data are evaluated and categorized to infer the relevant progress. Based upon the most influencing muscles, curve fitting is performed. Trajectory-based data points are collected through a scaled geometric Open-Sim musculoskeletal model that fits the subject’s anthropometric data. These data are found to be most suitable to prescribe relevant exercise and to design customized robotic assistance. Case studies demonstrate the approach’s efficacy, including optimally synthesized automated configuration for the desired trajectory.

A path planning method is presented based on non-autonomous dynamicmodeling of open-loops in articulated systems. It is assumed that one part ofthe mechanical system is submitted to specified motions laws, while movements ofthe complementary part are free. Thus, motion optimization is related to freejoint movements but it is achieved on the basis of the dynamic model of thewhole mechanical system. This approach introduces a non-autonomous stateequation of a special type in the sense that it can not only depend on therunning time but also on the unknown travelling time. The cost function to beminimized involves the travelling time and the actuating inputs. Optimization isachieved by applying the Pontryagin Maximum Principle which yields a newoptimality condition concerning the travelling time dependency of the statedproblem. Two simulation examples are presented. The first one shows how thedeveloped technique makes possible both the reducing and mastering the dynamiccomplexity of a four degrees of freedom-vertical manipulator. Set at fourdegrees of freedom, the second one deals with a redundant planar manipulatorcharacterized by a mobile base that is submitted to a specified drivingmotion.

We propose a hierarchical cognitive navigation model (HCNM) to improve the self-learning and self-adaptive ability of mobile robots in unknown and complex environments. The HCNM model adopts the divide and conquers approach by dividing the path planning task into different levels of sub-tasks in complex environments and solves each sub-task in a smaller state subspace to decrease the state space dimensions. The HCNM model imitates animal asymptotic properties through the study of thermodynamic processes and designs a cognitive learning algorithm to achieve online optimum search strategies. We prove that the learning algorithm designed ensures that the cognitive model can converge to the optimal behavior path with probability one. Robot navigation is studied on the basis of the cognitive process. The experimental results show that the HCNM model has strong adaptability in unknown and environment, and the navigation path is clearer and the convergence time is better. Among them, the convergence time of HCNM model is 25 s, which is 86.5% lower than that of HRLM model. The HCNM model studied in this paper adopts a hierarchical structure, which reduces the learning difficulty and accelerates the learning speed in the unknown environment.

This paper proposes a virtual reality-based dual-mode teleoperation architecture to assist human operators in remotely operating robotic manipulation systems in a safe and flexible way. The architecture, implemented via a finite state machine, enables the operator to switch between two operational modes: the Approach mode, where the operator indirectly controls the robotic system by specifying its target configuration via the immersive virtual reality (VR) interface, and the Telemanip mode, where the operator directly controls the robot end-effector motion via input devices. The two independent control modes have been tested along the task of reaching a glass on a table by a sample population of 18 participants. Two working groups have been considered to distinguish users with previous experience with VR technologies from the novices. The results of the user study presented in this work show the potential of the proposed architecture in terms of usability, both physical and mental workload, and user satisfaction. Finally, a statistical analysis showed no significant differences along these three metrics between the two considered groups demonstrating ease of use of the proposed architecture by both people with and with no previous experience in VR.

The venous blood test is a prevalent auxiliary medical diagnostic method. Venous blood collection equipment can improve blood collection’s success rate and stability, reduce the workload of medical staff, and improve the efficiency of diagnosis and treatment. This study proposed a rigid-flexible composite puncture (RFCP) strategy, based on which a small 7-degree-of-freedom (DOF) auxiliary venipuncture blood collection (VPBC) robot using a trocar needle was designed. The robot consists of a position and orientation adjustment mechanism and a RFCP end-effector, which can perform RFCP to avoid piercing the blood vessel’s lower wall during puncture. The inverse kinematics solution and validation of the robot were analyzed based on the differential evolution algorithm, after which the quintic polynomial interpolation algorithm was applied to achieve the robot trajectory planning control. Finally, the VPBC robot prototype was developed for experiments. The trajectory planning experiment verified the correctness of the inverse kinematics solution and trajectory planning, and the composite puncture blood collection experiment verified the feasibility of the RFCP strategy.

The reconfigurable mechanisms can satisfy the requirements of changing environments, working conditions, and tasks on the function and performance of the mechanism and can be applied to machine tool manufacturing, space detection, etc. Inspired by the single-vertex fivefold origami pattern, a new reconfigurable parallel mechanism is proposed in this paper, which has special singular positions and stable motion due to replicating the stabilizing kinematic properties of origami. Through analyzing the topologic change of the folding process of the pattern and treating it as a reconfigurable joint, a new reconfigurable parallel mechanism with 3, 4, 5, or 6 degrees of freedom is obtained. Then, the kinematics solution, workspace, and singularity of the mechanism are calculated. The results indicate that the singular configuration of the origami-derived reconfigurable parallel mechanism is mainly located in a special plane, and the scope of the workspace is still large after the configuration change. The mechanism has the potential to adapt to multiple tasks and working conditions through the conversion among different configurations by folding reconfigurable joints on the branch chain.

This paper investigates the influence of adding an upper body to a bipedal robot on its stable walking behavior. The robot’s parts are mutually interconnected through an actuator network system. Therefore, the movement pattern of the upper body depends on the type of interactions created with other limbs. Throughout the experiments, various interactions among the different body parts were tested. The results showed that a robot with a motionless upper body exhibited unstable walking behavior. However, once the same upper body was involved and interacted properly, with other body parts, its movement significantly helped to stabilize the behavior of the robot.

Hyper-redundant robots have good prospects for applications in confined space due to their high flexibility and slim body size. However, the super-redundant structure brings great challenges for its inverse kinematics with shape constraints. Unfortunately, traditional Jacobian pseudo-inverse-based inverse kinematics method and forward and backward reaching inverse kinematics (FABRIK) method are difficult to constrain the arm shape and realize trajectory tracking in confined spaces. To solve this problem, we propose a shape-controllable FABRIK method to satisfy the given path and shape constraints. Firstly, the kinematic model of the hyper-redundant robot is established, and the canonical FABRIK method is introduced. Based on the preliminary works, the single-layer improved FABRIK method is developed to solve the position and pointing inverse kinematics considering path environment and joint angle constraints instead of two-layer geometric iterations. For tracking the desired end roll angles, the polygonal virtual arm is designed. The real arm roll angle is achieved by controlling its winding on the virtual arm. In this way, the shape can be controlled. Finally, we compare the proposed method with other three approaches by simulations. Results show that the proposed method is more efficient and the arm shape is controllable.

Zero moment point (ZMP) is the most popular concept that is applied to stabilize the gait motion of a biped robot. This paper utilizes ZMP with the augmented-reality (AR) method to improve the stability of gait motion of a biped robot. The 3ds Max computer software package is used to build a virtual robot. Under an achieved joint angle data of solid robot to produce an animation of the robot's trajectory, the joint angle data are transmitted to the virtual robot to analyze the offset of the trunk. Furthermore, this investigation adopts AR to allow the user to make direct comparisons between the solid and virtual robot before and after the gait motion is corrected. The animated trajectories of the virtual robot are compared and the relevant data provide feedback to the solid robot to adjust the joint angle and further correct its posture. The experimental results reveal that the proposed scheme can improve gait motion, even when the biped robot is affected by an unexpected loading disturbance. As well as improving the stability of gait motion of a biped robot, the results of this study can also be used to teach the application of the proposed method in a robotics class.

In various industrial robotic applications, the effective traversal of a manipulator amidst obstacles and its ability to reach specific task-points are imperative for the execution of predefined tasks. In certain scenarios, the sequence in which the manipulator reaches these task-points significantly impacts the overall cycle time required for task completion. Moreover, some tasks necessitate significant force exertion at the end-effector. Therefore, establishing an optimal sequence for the task-points reached by the end-effector’s tip is crucial for enhancing robot performance, ensuring collision-free motion and maintaining high-force application at the end-effector’s tip.

To maximize the manipulator’s manipulability, which serves as a performance index for assessing its force capability, we aim to establish an optimal collision-free task sequence considering higher mechanical advantage. Three optimization criteria are considered: the cycle time, collision avoidance and the manipulability index. Optimization is accomplished using a genetic algorithm coupled with the Bump-Surface concept for collision avoidance. The effectiveness of this approach is confirmed through simulation experiments conducted in 2D and 3D environments with obstacles employing both redundant and non-redundant robots.

This work describes a hierarchically structured geometric database in an off-line robot programming system. The data structure contains the numerical definition of the frame variables, as well as an indicator of the respective reference frames. Moreover, the physical relations between the objects in the environment are included. The database is implemented such that it continuously reflects the actual structure of the environment. As a result, all calculations of the frame locations are carried out automatically. Moreover, the programming system is capable to autonomously updating the numerical information after changes in the environment. Making this database the heart of a robot programming system greatly simplifies the off-line programming of complex robot tasks, like f.i. assembly tasks.

This article presents the development of a robot capable of modifying its size through a wheel reconfiguration strategy. The reconfigurable wheel design is based on a four-bar retractable mechanism that achieves variation of the effective radius of the wheel. A reconfiguration index is introduced based on the number of retractable mechanisms that predicts the radius of configuration according to the number of mechanisms implemented in the wheel. The kinematics of the retractable mechanism is studied to determine the theoretical reconfiguration radius during the transformation process, it is also evaluated numerically with the help of the GeoGebra software, and it is validated experimentally by image analysis using the Tracker software. The transformation process of the robot is investigated through an analysis of forces that consider the wheel in contact with the obstacle, the calculation of the wheel torque and the height of the obstacle to be overcome are presented. On the other hand, the experimental validation of the robot reconfiguration process is presented through the percentage of success shown by the robot to overcome obstacles of 50, 75, 100 and 125 mm. In addition, measurements of energy consumption during the transformation process are reported. Reconfigurable wheels, capable of adapting their size, offer innovative solutions to various challenges across different applications such as robotic exploration and search and rescue missions to industrial settings. Some key issues that these wheels can address include terrain adaptability enhancing a robot’s mobility over uneven surfaces, or obstacles; enhanced robotic design; cost-effective design; space efficiency; and versatility in applications.