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Upper-limb joint kinematics are highly complex and the kinematics of rehabilitation exoskeletons fail to reproduce them, resulting in hyperstaticity and human–machine incompatibility. The purpose of this paper is to design and develop a compatible exoskeleton robot (Co-Exos II) to address these problems.

The configuration synthesis of Co-Exos II is completed using advanced mechanism theory. A compatible configuration is selected and four passive joints are introduced into the connecting interfaces based on optimal configuration principles. A Co-Exos II prototype with nine degrees of freedom (DOFs) is developed and still owns a compact structure and volume. A new approach is presented to compensate the vertical glenohumeral (GH) movements. Co-Exos II and the upper arm are simplified as a guide-bar mechanism at the elevating plane. The theoretical displacements of passive joints are calculated by the kinematic model of the shoulder loop. The compatible experiments are completed to measure the kinematics of passive joints.

The compatible configuration of the passive joints can effectively reduce the gravity influences of the exoskeleton device and the upper extremities. The passive joints exhibit excellent compensation effect for the GH joint movements by comparing the theoretical and measured results. Passive joints can compensate for most GH movements, especially vertical movements.

Co-Exos II possesses good human–machine compatibility and wearable comfort for the affected upper limbs. The proposed compensation method is convenient to therapists and stroke patients during the rehabilitation trainings.

The purpose of this paper is to evaluate three categories of four-degrees of freedom (4-DOFs) upper limb rehabilitation exoskeleton mechanisms from the perspective of relative movement offsets between the upper limb and the exoskeleton, so as to provide reference for the selection of exoskeleton mechanism configurations.

According to the configuration synthesis and optimum principles of 4-DOFs upper limb exoskeleton mechanisms, three categories of exoskeletons compatible with upper limb were proposed. From the perspective of human exoskeleton closed chain, through reasonable decomposition and kinematic characteristics analysis of passive connective joints, the kinematic equations of three categories exoskeletons were established and inverse position solution method were addressed. Subsequently, three indexes, which can represent the relative movement offsets of human–exoskeleton were defined.

Based on the presented position solution and evaluation indexes, the joint displacements and relative movement offsets of the three exoskeletons during eating movement were compared, on which the kinematic characteristics were investigated. The results indicated that the second category of exoskeleton was more suitable for upper limb rehabilitation than the other two categories.

This paper has a certain reference value for the selection of the 4-DOFs upper extremity rehabilitation exoskeleton mechanism configurations. The selected exoskeleton can ensure the safety and comfort of stroke patients with upper limb dyskinesia during rehabilitation training.

The purpose of this paper is to propose a new methodological framework within which a compliant robotic joint can be studied.

A new method is presented for detecting the direction of the robotic joint rotation when subjected to an external collision force.

The behaviour of the silicone rubber shows strong non‐linearity, therefore, the sensor‐elements cannot be used for accurate measurements.

A new type of safe robotic mechanisms with an internal measuring system is proposed in this paper.

Underactuated fingers are adapted to generate several grasping modes for different tasks, and coupled fingers and self-adaptive fingers are two important types of them. Aiming to expand the application and increase adaptability of robotic hand, this paper aims to propose a novel grasping model, called coupled and indirectly self-adaptive (CISA) grasping model, which is the combination of coupled finger and indirectly self-adaptive finger.

CISA grasping process includes two stages: first, coupled and then indirectly self-adaptive grasping; thus, it is not only integrated with the good pinching ability of coupled finger but also characterized with the high flexibility of indirectly self-adaptive finger. Furthermore, a CISA hand with linkage-slider, called CISA-LS hand, is designed based on the CISA grasping model, consisting of 1 palm, 5 CISA-LS fingers and 14 degrees of freedom.

To research the grasping behavior of CISA-LS hand, kinematic analysis, dynamic analysis and force analysis of 2-joint CISA-LS finger are performed. Results of grasping experiments for different objects demonstrate the high reliability and stability of CISA-LS hand.

CISA fingers integrate two grasping modes, coupled grasping and indirectly self-adaptive grasping, into one finger. And a double-linkage-slider mechanism is designed as the switch device.

This paper aims to propose a novel hand to bridge the gap between the traditional rigid robot hands and the soft hands to obtain a better grasping performance.

The proposed hand consists of three fingers. Each finger has 15 degrees of freedom and three phalanxes, which can bend in one direction when load is applied, but they are rigid toward the opposite direction at the initial position. The grasping process and simulations of the fingers are discussed in this paper. Both kinematic and dynamics analyses are performed to predict the performance of the hand. Subsequently, a prototype of the hand is developed for experiments.

Both kinematics and dynamics analyses indicate good grasping performance of the hand. Simulations and experiments confirm the feasibility of the finger design. The hand can execute hybrid grasping modes with more uniform force distribution and a larger workspace than traditional rigid fingers. The proposed hand has much potential in the industrial sector.

A new method to obtain better grasping performance and to bridge the gap between the rigid finger and the soft finger has been presented and verified. The hand combines the advantages of both the rigid phalanxes and the soft fingers. Compared with some traditional rigid fingers, the proposed design has a more uniform force distribution and a bigger workspace.

This paper aims to get rid of the traditional basic principle of using the motor as the variable stiffness drive source, simplify the structure of the exoskeleton and reduce the quality of the exoskeleton. This paper proposes to use shape memory alloys (SMA) as the variable stiffness drive source.

In this study, SMA is used to construct the active variable stiffness unit, the Brinson constitutive model is used to establish a dynamic model to control the active variable stiffness unit and the above active variable stiffness unit is used to realize the force control function and construct a lightweight, variable stiffness knee exoskeleton.

The dynamic model constructed in this paper can preliminarily describe the phase transformation process of the active variable stiffness unit and realize the variable stiffness function of the knee exoskeleton. The variable stiffness exoskeleton can effectively reduce the driving error under the high-speed walking condition.

The contribution of this paper is to combine SMAs to construct an active variable stiffness unit, build a dynamic model for controlling the active variable stiffness unit and construct a lightweight, variable stiffness knee exoskeleton.

The purpose of this paper is to present a design of climbing robot with magnetic wheels which can move on the surface of steel bridge. The locomotion concept is based on adapted lightweight magnetic wheel units with relatively high attractive force and friction force.

The robot has the main advantages of being compact (352 × – 215 × – 155 mm), lightweight (2.3 kg without battery) and simple mechanical structure. It is not only able to climb vertical walls and follow circumferential paths, but also able to pass complex obstacles such as bolts, steps, convex and concave corners with almost any inclination regarding gravity. By using a servo as a compliant joint, the wheel base can be changed to enable the robot to overcome convex corners.

The experiment results show that the climbing robot has a good performance on locomotion, and it is successful in negotiating the complex obstacles. On the other hand, the limitations in locomotion of the robot are also presented.

Compared with the past researches, the robot shows good performance on overcoming complex obstacles such as concave corners, convex corners, bolts and steps on the steel bridge. Magnetic wheel with the characterization of compact size and lightweight is able to provide bigger adhesion force and friction coefficient.

The purpose of this paper is to present new locomotion and steering modules conceived and designed for rescue serpentine robots with enhanced climbing ability. The locomotion modules apply sock locomotion technology that allows great motion efficiency in rubble and confined environment due to the very high propulsion ratio. The steering joints guarantee good orientation dexterity by exploiting actuation based on smart materials.

Great attention and time is dedicated to the design phase, digital mock‐upping and virtual comparative assessment of different solutions. Mechatronic interdisciplinary design methodology including mechanisms analysis, sensory actuation issues and functional materials characterization, control and communication integration has been adopted.

The locomotion modules are revised and updated versions improving climbing ability of the socked locomotion module originally proposed by the authors. New steering modules with high orientation workspace, based on smart actuation, are introduced.

The evaluation of the findings on the field is planned but no experimental result is today available.

Agile serpentine robots are requested for quick and safe rescue and special risky interventions in environments where dense vegetation, rubble and confined spaces prevent human presence. These robots offer invaluable potential help in such risky interventions mainly by being agile in exploring the environment, robust, low cost, reliable, and tele‐operated.

The paper presents original issues in terms of concept and design of instrumental (locomotion and steering) modules for composing modular rescue robots with very high locomotion agility and climbing performances.

This paper aims to use different machine learning (ML) algorithms for the prediction of inverse kinematic solutions in parallel manipulators (PMs) to overcome the computational difficulties and approximations involved with the analytical methods. The results obtained from the ML algorithms and the Denavit–Hartenberg (DH) approach are compared with the experimental results to evaluate their performances. The study is performed on a novel 6-degree of freedom (DoF) PM that offers precise motions with a large workspace for the end effector.

The kinematic model for the proposed 3-PPSS PM is obtained using the modified DH approach and its inverse kinematic solutions are determined using the Levenberg–Marquardt algorithm. Various prediction algorithms such as the multiple linear regression, multi-variate polynomial regression, support vector, decision tree, random forest regression and multi-layer perceptron networks are applied to predict the inverse kinematic solutions for the manipulator. The data set required to train the network is generated experimentally by recording the poses of the end effector for different instantaneous positions of the slider using the concept of ArUco markers.

This paper fully demonstrates the possibility to use artificial intelligence for the prediction of inverse kinematic solutions especially for complex geometries.

As the analytical models derived from the geometrical method, Screw theory or numerical techniques involve approximations and needs more computational power, it is not advisable for real-time control of the manipulator. In addition, the data set obtained from the derived inverse kinematic equations to train the network may lead to inaccuracies in the predicted results. This error may generate significant deviations in the end-effector position from the desired position. The present work attempts to resolve this issue by proposing a camera-based approach that uses ArUco library and ML algorithms to create the data set experimentally and predict the inverse kinematic solutions accurately.

The purpose of this paper is to propose two simple tools for the kinematic characterization of hexapods. The paper also aims to share the experience of converting a popular commercial motion base (Stewart‐Gough platform, hexapod) to an industrial robot for use in heavy duty aerospace manufacturing processes.

The complete workspace of a hexapod is a six‐dimensional entity that is impossible to visualize. Thus, nearly all hexapod manufacturers simply state the extrema of each of the six dimensions, which is very misleading. As a compromise, a special 3D subset of the complete workspace is proposed, an approximation of which can be readily obtained using a computer‐aided design (CAD)/computer‐aided manufacturing (CAM) software suite, such as computer‐aided 3D interactive application (CATIA). While calibration techniques for serial robots are readily available, there is still no generally agreed procedure for calibrating hexapods. The paper proposes a simple calibration method that relies on the use of a laser tracker and requires no programming at all. Instead, the design parameters of the hexapod are directly and individually measured and the few computations involved are performed in a CAD/CAM software such as CATIA.

The conventional octahedral hexapod design has a very limited workspace, though free of singularities. There are important deviations between the actual and the specified kinematic model in a commercial motion base.

A commercial motion base can be used as a precision positioning device with its controller retrofitted with state‐of‐the‐art motion control technology with accurate workspace and geometric characteristics.

A novel geometric approach for obtaining meaningful measures of the workspace is proposed. A novel, systematic procedure for the calibration of a hexapod is outlined. Finally, experimental results are presented and discussed.