As an important basic component of quadruped robots, mechanical legs provide the robots with excellent maneuverability and versatility, which determine the core application performance such as job adaptability, walking speed, and load capacity. A large number of robotics institutes for the last few decades have studied mechanical legs used by quadruped robots and published many research results. In this article, we collect these research results and classify them into three categories (prismatic legs, articulated legs, and redundant articulated legs) according to the degrees of freedom and then introduce and analyze them. On this basis, we summarize and study the design methods of the actuators and mechanical leg structures. Finally, we make some suggestions for the development of quadruped robot’s legs in the future. The motivation of this review is to summarize and analyze previous research efforts and provide useful guidance for future robotic designers to develop more efficient mechanical legs of quadruped robots.

Due to the complex spatial hierarchy and large network scale of the mine ventilation system, it is difficult to obtain ventilation information of all branches in real-time, accurately, and comprehensively by arranging sensors. To overcome this difficulty, this paper proposes an optimal layout method of sensors based on the DETMAX algorithm and Tabu search algorithm. Given a known number of sensors, the proposed method can efficiently select an optimal set of branches to arrange these sensors according to the calculated airflow of each branch while considering both the air resistance error and the sensor error. This optimized sensor layout can minimize the airflow error of the undetected branches and obtain the ventilation information of the entire ventilation system accurately with a limited number of sensors. The proposed method has significant economic benefits and can provide technical support for developing intelligent ventilation systems. Finally, the performance and efficiency of this method are verified by comparing it with the Monte Carlo algorithm and the Ant Colony algorithm with data from the Wangjialing coal mine in China.

This article develops a bionic topology optimization method for engineering applications. Unlike traditional density-based methods, the real material density is used as a design variable, and its evolution is controlled by a simpler and improved bone remodelling formula. A calculation method of the threshold value in this formula is given that solves a problem difficult to define in engineering applications. A progressive function is constructed for solving the iterative fluctuation problem. A post-processing method based on the level set method is presented for the jagged boundary problem. Compared with the traditional bone remodelling algorithm, the proposed method has better optimization ability. Some examples prove the feasibility and effectiveness of the method. Moreover, the influence of some key parameters on the optimization is discussed.

From the perspective of bionics, a structural topology optimization method combining a bone remodelling algorithm and real engineering requirements is proposed. Through joint simulation using MATLAB and Ansys, this method uses explicit physical concepts and efficient computer solving capabilities, which makes it highly practical and simple. The effectiveness and feasibility of the method are verified by comparing topology optimizations performed on four classical examples and the optimized results from the 99 lines of topology optimization code. Next, some key parameters of the method are discussed in depth, laying the foundation for a deeper understanding and application of the method. The purpose of this article is to introduce a bionic theory into the field of topology optimization by implementing an easy-to-use and extensible numerical algorithm to promote the development of this technology, so that it can better realize its engineering value.

Displacement is an important measure of stiffness, and its constraint must be considered in many real engineering designs. However, traditional volume-constrained compliance minimization methods for load-bearing structures do not deal with displacements of practical importance directly. Based on this situation, the paper extends an improved bionic topology optimization method to solve the topology optimization problem with an additional displacement constraint. The updates of density design variables are based on an improved bone remodeling algorithm rather than gradient information employed by traditional methods. An explicit relationship between the threshold in the bone remodeling algorithm and target node displacement is constructed to satisfy displacement constraint. As a result, one will obtain a topology with an optimal cost-weighted sum of stiffness and mass while the target node displacement does not exceed its predefined limit. 2D and 3D examples are given to demonstrate the effectiveness of the proposed method.

This paper investigates the asynchronous H∞ control problem of discrete-time hidden Markov jump power systems (hMJPSs) under cyber attacks. To precisely capture the dynamic characteristics of transient faults and circuit breaker switching in power systems, a hidden Markov jump process with unknown information is introduced. A hybrid scheduling protocol via event triggering is proposed to enhance the utilization of communication resources. By dynamically adjusting the data transmission frequency of sensor nodes, the protocol significantly reduces communication resource usage while maintaining H∞ performance of the system. Additionally, considering the mode mismatched behavior between the power systems and the controllers, the asynchronous state-feedback controller is designed. Through the mode-dependent Lyapunov function, the sufficient conditions for the mean-square stability of hMJPSs are derived. Finally, the effectiveness and practicality of the proposed method are validated via simulation examples.