Advanced Research in Intelligent Autonomous Mobile Robots System, Learning and Control

Dear Colleagues,

In recent years, progress in the fields of robotics and AI have accelerated the introduction of mobile robots into our lives. By 2050, advancements in robotics and AI are predicted to be at a level that one cannot imagine, with robots becoming an indispensable part of daily life. The application of autonomous mobile robots is rapidly expanding to different fields, such as remote sensing, intelligent mobility devices, service robotics for homes and hospitality, surveillance, medical and healthcare, construction and infrastructure management, search and rescue, manufacturing, and warehouse management. Beyond that, we are witnessing advancements in robotic fields such as self-driving cars, agriculture robotics, forestry, and the ocean. In recent years, machine learning and computer vision methods have opened novel paradigms of artificial intelligence, allowing robotic systems flexible reasoning and improved autonomy in challenging scenarios. This has allowed robots not only to attain, but also generate cost-effective and super-efficient tasks with meticulous precision. However, most of these heterogeneous autonomous systems are increasingly employed in unstructured, cluttered, dynamic, and human-centric environments that are still challenging to handle. Therefore, many open challenges remain to be solved in this domain.

We are pleased to invite you to this Special Issue aiming to collect high-quality articles concerning some recent advances in the field of autonomous mobile robot systems. Through this Special Issue, we aim to cover a wide range of advanced topics, ranging from intelligent systems to advanced mechanisms and algorithms in robotics and mechatronics, including applications of deep learning and machine learning techniques for mobile-robotics-related problems. In this Special Issue, original research articles and reviews in regard to the state-of-the-art are welcome, with research areas including (but not limited to) the following:

• Mobile robotics, AI, and their applications in robotics;
• Mapping and localization or SLAM techniques;
• Path planning;
• Robot learning (deep learning/machine learning);
• Smart sensing and new sensor integration, IoT, etc.;
• Service robotics (including robots in healthcare and/or assistive
  devices);
• Haptics-, AR-, and VR-based systems;
• Advanced manipulation;
• Intelligent control;
• System integration and software architecture for autonomous systems;
• Field robotics;
• Multirobot systems, including heterogeneous robot systems.

Dr. Ankit A. Ravankar
Dr. Jose Victorio Salazar Luces
Dr. Abhijeet Ravankar
Guest Editors

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