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Teaching by demonstration (TbD) is a promising way for robot learning skills in human and robot collaborative hybrid manufacturing lines. Traditionally, TbD systems have only concentrated on how to enable robots to learn movement skills from humans. This paper aims to develop an extended TbD system which can also enable learning stiffness regulation strategies from humans.

Here, the authors propose an extended dynamical motor primitives (DMP) framework to achieve this goal. In addition to the advantages of the traditional ones, the authors’ framework can enable robots to simultaneously learn stiffness and the movement from human demonstrations. Additionally, Gaussian mixture model (GMM) is used to capture the features of movement and of stiffness from multiple demonstrations of the same skill. Human limb surface electromyography (sEMG) signals are estimated to obtain the reference stiffness profiles.

The authors have experimentally demonstrated the effectiveness of the proposed framework. It shows that the authors approach could allow the robot to execute tasks in a variable impedance control mode with the learned movement trajectories and stiffness profiles.

In robot skill acquisition, DMP is widely used to encode robotic behaviors. So far, however, these DMP modes do not provide the ability to properly represent and generalize stiffness profiles. The authors argue that both movement trajectories and stiffness profiles should be considered equally in robot skill learning. The authors’ approach has great potential of applications in the future hybrid manufacturing lines.

The purpose of this paper is to study the dynamic modeling and controller design for the series element actuator (SEA) joints. The robot equipped with SEA joints is a strong coupling, nonlinear, highly flexible system, which can prevent itself from damaging by the accidental impact and the people to be injured by the robot.

Based on the torque source model, the authors built a dynamic model for the SEA joint. To improve the accuracy of this model, the authors designed an elastic element into the joint and implemented the vector control for the joint motor. A control method of combined PD controller and back-stepping was proposed. Moreover, the torque control could be transformed into position control by stiffness transformation.

The established model and the proposed method are verified by the position and torque control experiments. The experimental results show that the dynamic model of the SEA joint is accurate and the proposed control strategies for the SEA joint are reasonable and feasible.

The main contribution of the paper is as follows: designing an elastic element with high linearity to improve the model accuracy of the SEA joint. The control strategy-based back-stepping method for the SEA joint is proposed to increase the robustness of the controller.

The purpose of this study is to research the effects of interrupted aging on the corrosion behavior of Al–Cu–Mg–Ag heat-resistant alloy by means of intergranular corrosion (IGC) testing, potentiodynamic polarization combined with optical microscopy and transmission electron microscopy.

The results show that the IGC began on the grain boundaries and continued along the grain boundary. The corrosion resistance property of Al–Cu–Mg–Ag alloy was enhanced by interrupted aging. The precipitations of the interrupted aged sample both in the grains and on the grain boundaries were fine, and the chain-like phases on the grain boundary were distributed nearly continuously.

The corrosion resistance of Al–Cu–Mg series Al alloy with equilibrium phase (Al₂Cu) is notably determined by precipitation-free zone (PFZ) as the self-corrosion potentials of (Al₂Cu), PFZ and the matrix satisfied the relation EPFZ < E_θ<EMatrix.

The connections of the PFZ on both sides of the grain boundary decreased the corrosion resistance of Al–Cu–Mg–Ag alloy treated by the single aging.

The purpose of this paper is to investigate the influence of the potential of hydrogen (pH) and dissolved oxygen in artificial seawater on the passivation behavior of 316L stainless steel.

The corrosion behavior was studied by using electrochemical measurements such as electrochemical impedance spectroscopy and polarization curve. The passive films were characterized with X-ray photoelectron spectroscopy.

The polarization resistance of the passive film decreases as the pH value drops ascribed to the formation of much more point defects. The donor carrier concentration (ND) in the passive film formed in the deaerated condition is lower than that in aerated conditions. Nevertheless, this phenomenon is the opposite when the pH value is 1 due to the significant decrease of Fe oxides/hydroxides coupled with the stable content of Cr oxides/hydroxides species. In addition, the compositional variation of the passive film also leads to the changes of its semiconductor properties from N-type to bipolar type.

This paper shows the variation of polarization resistance, corrosion potential, passive film composition and semiconductor properties with the pH value and dissolved oxygen. The results can serve as references to the further study on crevice corrosion of 316L in seawater.

The purpose of this study is to review and summarise the existing available literature on lightweight cladding systems to provide detailed information on fire behaviour (ignitibility, heat release rate and smoke toxicity) and various test method protocols. Additionally, the paper discusses the challenges and provides updated knowledge and recommendation on selective-fire mechanisms such as rapid-fire spread, air cavity and fire re-entry behaviours due to dripping and melting of lightweight composite claddings.

A comprehensive literature review on fire behaviour, fire hazard and testing methods of lightweight composite claddings has been conducted in this research. In summarising all possible fire hazards, particular attention is given to the potential impact of toxicity of lightweight cladding fires. In addition, various criteria for fire performance evaluation of lightweight composite claddings are also highlighted. These evaluations are generally categorised as small-, intermediate- and large-scale test methods.

The major challenges of lightweight claddings are rapid fire spread, smoke production and toxicity and inconsistency in fire testing.

The review highlights the current challenges in cladding fire, smoke toxicity, testing system and regulation to provide some research recommendations to address the identified challenges.

This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications. This study designed the exoskeleton cloud-brain platform and validated its safety assessment.

According to the dimension of data and the transmission speed, this paper implements a three-layer cloud-brain platform of exoskeleton based on Alibaba Cloud's Lambda-like architecture. At the same time, given the human–machine safety status detection problem of the exoskeleton, this paper built a personalized machine-learning safety detection module for users with the multi-dimensional sensor data cloned by the cloud-brain platform. This module includes an abnormality detection model, prediction model and state classification model of the human–machine state.

These functions of the exoskeleton cloud-brain and the algorithms based on it were validated by the experiments, they meet the needs of use.

This thesis innovatively proposes a cloud-brain platform for exoskeletons, beginning the digitalization and intelligence of the exoskeletal rehabilitation process and laying the foundation for future intelligent assistance systems.