###### Abstract  
Robotics research has a unique allure for both academia and the industry due to its potential for groundbreaking innovation and real-world applications [1,2]. Robotics research and applications encompass a broad range of topics, challenges, and opportunities. The topics in this Special Issue represent just a small fraction of the diverse and interdisciplinary field of robotics, which intersects with areas such as materials science and mechatronics, computer science, hardware engineering, robot kinematics, and bionics [3,4]. Fast-paced development in sensor hardware, robot perception, smart decision-making strategy, and gripper designs allows robots to react in \"real-time\" to the environment and thus work intelligently alongside human beings [5]. More crucially, artificial intelligence (AI) integrated into robotic applications has the potential to revolutionize various aspects of human life, offering a wide range of benefits and support. This Special Issue of _Applied Sciences_, entitled \"Recent Advances in Robotics and Intelligent Robots Applications\", has 14 research papers, covering topics from bionics (contribution 1) and soft-material robot designs (contribution 14), infrared image algorithms (contribution 2), target tracking algorithms (contribution 3 and 7), hyperspectral image classification (contribution 4), manipulator control (contribution 5 and 8), and space image denoise and analysis methods (contribution 6 and 10) to motion and path planning (contribution 9, 11, 12, and 13). The demonstrated robot designs and algorithm development include novel low-cost robot designs with leaping abilities (contribution 1) and resilient meta-materials (contribution 14); an accurate model that identifies the thermal target (contribution 2); sophisticated neutral network models that track solar positions with time scales (contribution 3); pixel-level hyperspectral image classification with neural networks (contribution 4); space manipulator control models in orbit (contribution 5); and image denoise methods for sky-based backgrounds (contribution 6); visual object tracking with convolution and correlation (contribution 7); pick-and-place models with small dataset training (contribution 8); mathematic models for continuum robots (contribution 9); analyses of the MTF of remote sensing cameras (contribution 10); time-varying method for global path planning (contribution 11); low-cost localization models with a sparse modular point matrix (SMPM) (contribution 12); and deep reinforcement learning combined with RRT for path planning (contribution 13). The spectrum of the contributed research spans a wide range of topics, from traditional image processing methods and robot designs to robot kinematic models and path and motion planning with deep learning approaches. Soft robotics focuses on the research and development of robots with compliant and flexible structures that are inspired by natural organisms. These robots can better adapt to dynamic environments and are often used in applications such as medical robotics, search and rescue tasks, and outdoor exploration [6]. Similarly, bio-inspired robotics draws inspiration from biology to design robots that mimic the structure and behavior of living organisms. This includes biomimetic locomotion,sensory systems inspired by animal perception, and soft actuators inspired by muscles and tendons [7]. Manipulation focuses on the development of robotic arms and hands that are capable of grasping, manipulating, and interacting with objects in a dexterous and precise manner. Primary applications include industrial automation, warehouse logistics, and assistive robotics for space applications [8]. Motion planning involves the algorithms and techniques used to plan the path of a robot from the current state to a desired state while avoiding obstacles and adhering to constraints without any human intervention.