*2.2. Service Robotics*

Service robots [1] are gaining popularity and significantly impacting how businesses operate and humans interact with technology. In the hospitality industry, robots are now employed to carry out room service, reception duties and concierge services. In healthcare, robots assist in patient care, including as nanoelectromechanical devices for medical applications [8], in rehabilitation support [9,10] and in surgical robotics [11]. Moreover, service

**Citation:** Gracia, L.; Perez-Vidal, C. Special Issue on Trends and Challenges in Robotic Applications. *Appl. Sci.* **2023**, *13*, 9131. https:// doi.org/10.3390/app13169131

Received: 4 August 2023 Accepted: 9 August 2023 Published: 10 August 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

robots are also making inroads in agriculture [12], retail and public spaces, presenting new opportunities for automation in areas that previously relied solely on human labor.

Robotic rehabilitation is a challenging field that involves a transversal flow of knowledge with other robotic technologies. For example, the similarity between lower limb rehabilitation robotics and humanoid auto-balanced walking robotics [13] lies in their focus on stability and balance. Both lower limb rehabilitation robotics and humanoid autobalanced walking robotics prioritize maintaining stability and balance during movement. In lower limb rehabilitation robotics, ensuring the patient's safety and preventing falls are crucial aspects of the rehabilitation process. The robot's control algorithms and mechanical design are geared towards providing stable and controlled movements during therapy sessions. On the other hand, humanoid auto-balanced walking robotics aims to replicate human-like walking patterns while autonomously maintaining balance. These robots often have advanced sensors, such as inertial measurement units (IMUs), cameras and force/torque sensors, to continually assess their orientation and stability during walking. Advanced control algorithms are employed to adjust the robot's posture and foot placement in real-time, ensuring balance and stability, even on uneven or challenging terrain. Technologies and insights developed in one field can potentially inform and improve the other, fostering cross-disciplinary advancements in robotics research [14].

#### *2.3. Computer Vision and Other Advanced Techniques*

Computer vision focuses on enabling computers to interpret and understand visual information from the world, including objects and humans [15]. It involves the development of algorithms and techniques that allow machines to process, analyze and extract meaningful insights from images and videos. In recent years, computer vision has undergone significant advancements, leading to the emergence of new technologies that allow for new interaction applications; for example, in [16], a moving object is manipulated by means of batting primitive to play table tennis with a human player.

Pose estimation is a fundamental concept in computer vision that involves determining the position and orientation of an object or a camera relative to a specific coordinate system. It plays a crucial role in various applications, such as augmented reality [17], robotics, 3D scene reconstruction and human–computer interaction. In simple terms, pose estimation aims to answer the question: "Where is the object or camera located, and how is it oriented in 3D space?" To achieve this, computer vision algorithms analyze visual data, typically in the form of images or videos, and extract relevant features or keypoints from the objects of interest. Similarly, [18] presents an interesting approach to pose computation using a 3D reconstruction of data obtained using an RGB-D multi-camera. A groundbreaking piece of technology that is currently attracting attention due to its relatively low cost is Time-of-Flight (ToF) sensing, and the authors of [19] present a multi-perspective ToF laser ranging system using prisms and mirrors.

The authors of [20] discuss the significance of 6D pose estimation in industry and its application in functions like bin picking and autopilot. They highlight the evolution of various approaches, both learning-based and non-learning-based, and aim to provide an up-to-date, thorough review of methods for 6D pose estimation, as well as the challenges and future trends in this field. Their paper compares the performance of different methods and categorizes them into two types of approach: non-learning-based and learning-based.

Using data from external sensors that measure 3D/6D locations is crucial to determining robots' kinematic parameters and the transformation between the world coordinate frame and the robot base. The study presented in [21] shows that full pose measurements result in significantly smaller robot orientation errors compared to using 3D data alone, while the robot position errors remain similar in both cases.

#### *2.4. Mobile Robots*

Mobile robots, including autonomous vehicles, are an exciting and rapidly evolving technology that has the potential to revolutionize robotic transportation. As research and development in this field progress, several new topics are emerging that address the challenges and enhance the capabilities of autonomous mobile robots, including swarm robotics and its tools [22]. Examples of this flourishing field of research include [23], which is focused on automatically allocating space for parking autonomous and human-operated vehicles, and [24], which presents a control system developed to achieve mobile robot formations based on the leader–follower method. In [25], a LiDAR sensor is proposed to navigate featured environments.

A special case of this technology is robotic navigation inside tunnels and mines. The authors of [26] present a localization and navigation system for autonomous dump vehicles in tunnels. This work also presents an autonomous load system for this kind of vehicle [27].

#### *2.5. Other Advanced Tools in Robotics*

Advanced tools for robotics applications encompass a wide range of software and hardware technologies that enhance the capabilities and efficiency of robotic systems. These tools are designed to streamline development, improve control, and enable robots to carry out complex tasks with higher precision. For instance, the authors of [28] use robot audition methods in order to estimate the elevation and azimuth angles of birds' vocalizations.

In [29], the authors propose a new stochastic method that efficiently tracks the desired end-effector task-space motions for mechanisms with redundant actuation and is applicable to industrial and collaborative robots. It utilizes manipulability measures and null-space configurations to achieve better manipulability, together with a collision-free trajectory in the task-space, providing a computationally tractable alternative to optimal motion planning, and demonstrated promising results in simulations and real robot scenarios.

Kinematics is a fundamental aspect of robotics because it deals with the study of robots' mechanical link motions. The work presented in [30] discusses the challenges in selecting structural parameters for artificial neural networks, which often relies on trial-and-error procedures. It presents a design method based on neural networks and Genichi Taguchi's approach, which is applied to solving inverse kinematics in a robotic manipulator, leading to improved result accuracy with a prediction percentage above 90% and a margin of error under 5%.

#### **3. Conclusions**

The future of robotics is exciting and promising, with the discussed trends in robotic applications continuing to unfold. From collaborative robots enhancing workplace safety to AI-powered robots driving intelligent automation and service robots revolutionizing industries, the impact of robotics is becoming increasingly pervasive. As technology advances and becomes more accessible, we can expect robots to play an even more significant role in transforming various aspects of human life, contributing to a more efficient, productive, and innovative world. However, with these advancements also come ethical considerations and the need for thoughtful regulations to ensure the responsible and beneficial integration of robots into society.

#### **4. Statistical Data**

This Special Issue on "Trends and Challenges in Robotic Applications" focuses on a wide range of robotics applications. In total, 39 papers were received between 20 August 2020 and 16 February 2023. After the reviewing process, 30 papers were accepted and 9 were not accepted, indicating an acceptance ratio of 76.9%. The accepted papers originated from research centers based mainly in Latin America, Europe and China.

**Author Contributions:** Conceptualization, L.G. and C.P.-V.; investigation, L.G. and C.P.-V.; writing original draft preparation, L.G. and C.P.-V.; writing—review and editing, L.G. and C.P.-V.; visualization, L.G. and C.P.-V.; supervision, L.G. and C.P.-V.; funding acquisition, L.G. and C.P.-V.; All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was partially funded by the Spanish Government (Grant PID2020-117421RB-C21, funded by MCIN/AEI/10.13039/501100011033).

**Acknowledgments:** The Guest Editors would like to thank all the authors and reviewers who contributed to this Special Issue for their valuable work in disseminating and curating the information contained within it. The Guest Editors also thank the *Applied Sciences* journal for trusting them to manage this publication.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
