Summary: There have been significant interests and efforts in the field of impedance control on robotic manipulation over last decades. Impedance control aims to achieve the desired mechanical interaction between the robotic equipment and its environment. This paper gives the overview and comparison of basic concepts and principles, implementation strategies, crucial techniques, and practical applications concerning the impedance control of robotic manipulation. This work attempts to serve as a tutorial to people outside the field and to promote discussion of a unified vision of impedance control within the field of robotic manipulation. The goal is to help readers quickly get into the problems of their interests related to impedance control of robotic manipulation and to provide guidance and insights in finding appropriate strategies and solutions.

A point cloud as a collection of points is poised to bring about a revolution in acquiring and generating three-dimensional (3D) surface information of an object in 3D reconstruction, industrial inspection, and robotic manipulation. In this revolution, the most challenging but imperative process is point could registration, i.e., obtaining a spatial transformation that aligns and matches two point clouds acquired in two different coordinates. In this survey paper, we present the overview and basic principles, give systematical classification and comparison of various methods, and address existing technical problems in point cloud registration. This review attempts to serve as a tutorial to academic researchers and engineers outside this field and to promote discussion of a unified vision of point cloud registration. The goal is to help readers quickly get into the problems of their interests related to point could registration and to provide them with insights and guidance in finding out appropriate strategies and solutions.

Collaborative robots have promising potential for widespread use in small-and-medium-sized enterprise (SME) manufacturing and production due to the development of increasingly sophisticated Human-Robot Collaboration technologies. However, predicting and identifying the behavior of collaborative robots remains a challenging problem due to the significant non-linear properties of their unique gearbox, the harmonic drive. To tackle the engineering problem, this work proposes a physics-informed neural network (PINN) to predict and identify collaborative robot joint dynamics. The procedure involves deriving the state-space dynamic model, embedding the system's dynamics into a recurrent neural network (RNN) with customized Runge-Kutta cells, obtaining labeled training data, predicting system responses, and estimating dynamic parameters. The proposed method is applied to predict and identify collaborative robot joint dynamics, and the results are verified and validated through numerical simulations and experimental testing, respectively. The obtained results demonstrate a high level of agreement with the ground truth and exhibit superior performance compared to the conventional PINN and the non-linear grey-box state-space estimation algorithm when confronted with non-linearity and dynamic coupling. Moreover, the PINN exhibits the potential for extension to various dynamic systems.

This paper presents the modelling and design analysis of V- and Z-shaped electrothermal microactuators. First, a comprehensive but concise closed-form multiphysical analytical model is developed to predict the output displacement and force of both V- and Z-shaped electrothermal microactuators operating either in vacuum or in air conditions. The analytical model is verified by finite element analysis and experimental testing. Then, a novel comparison benchmark is proposed for the design and analysis of the V- and Z-shaped microactuators. With the multiphysical model and comparison benchmark, comprehensive performance comparison and analysis of the V- and Z-shaped beams are performed with the aim of providing insight and guidance on selection and design of the two typical types of electrothermal microactuators. Finally, the application of the comparison model into the design analysis is demonstrated using a design example of an electrothermal microactuator, and the detailed investigation is conducted to examine the effects of the material properties and structural parameters on the microactuator outputs.