With the support for sustainable development of autonomous and intelligent systems, mechatronics, embedded systems, and robotics are becoming one hot research area. In this special issue, we select 35 papers among a large number of submissions. The selected papers cover several key technology areas in mechatronics and embedded systems and can be divided into the following eight categories.
Seven papers are related to autonomous and intelligent embedded systems. In the paper titled “Discrete Planning Unit Look-Ahead Velocity Control Strategy and Parallelization Research Based on GPU,” the GPU technology is introduced into CNC algorithms. In the paper titled “One Nonlinear PID Control to Improve the Control Performance of a Manipulator Actuated by a Pneumatic Muscle Actuator,” the controller is applied to the manipulator and experiments are conducted. In the paper titled “FPGA Implementation of Self-Organized Spiking Neural Network Controller for Mobile Robots,” a novel mechanism for controlling mobile robots is presented based on self-organized spiking neural network (SOSNN) and a method for FPGA implementation of this SOSNN is given. In the paper titled “Inner-Learning Mechanism Based Control Scheme for Manipulator with Multitasking and Changing Load,” the inner-learning mechanism makes the subcontrollers learn from the working controller when load changes so that the switching action causes smaller tracking error compared with the traditional switch controller. In the paper titled “Research on Architecture of the Prosthesis Shaping Equipment Control System,” the new software/hardware architecture of a five-axis high performance NC system is proposed. In the paper titled “Design and Development of the Humanoid Robot BHR-5,” the mechanical and control system design of the latest humanoid robot platform, BHR-5, is presented. In the paper titled “Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System,” an adaptive iterative learning control strategy is proposed to integrate with saturation-based robust control for uncertain robot system in presence of modeling uncertainties, unknown parameter, and external disturbance under alignment conditions.