Smart Robotics and Autonomous Systems

Dear Colleagues,

The field of smart robotics and autonomous systems is experiencing rapid advancements, driven by significant research in several key areas. Central to these advancements are robot perception, recognition, guidance, navigation, mapping, and localization, which are fundamental for enabling robots to comprehend and interact with their surroundings. These capabilities are indispensable for autonomous systems to operate efficiently in dynamic and unpredictable environments. Enhancing this efficiency further, multi-robot task assignment and allocation facilitate coordinated efforts, allowing multiple robots to work together seamlessly on complex tasks that surpass the abilities of a single robot.

Incorporating bio-inspired neural networks and evolutionary computation, along with cutting-edge artificial intelligence (AI), robotics researchers are developing more adaptive and resilient systems. These technologies enable learning-based robot decision-making, which is essential for robots to operate autonomously and make real-time adjustments based on their understanding of the environment and situational context. The synergy of these elements facilitates advanced cooperation among robots, ensuring they can work together seamlessly in diverse scenarios.

Human–robot teaming and interaction represent another vital research focus, examining how robots and humans can collaborate effectively. This area is particularly important for applications that require human oversight or partnership, such as in medical procedures, industrial processes, or rescue missions. The integration of AI and machine learning into robotic systems not only enhances their operational capabilities but also improves their ability to understand and predict human actions, leading to more intuitive and efficient interactions.

In an effort to disseminate the latest advancements in smart robotics and autonomous systems, a Special Issue in this area is proposed. This Special Issue will provide a platform for scientists, engineers, and industrial practitioners to present their most recent theoretical and technological developments. By focusing on key topics such as robot perception, multi-robot coordination, bio-inspired neural networks, learning-based decision-making, and human–robot interaction, this Special Issue aims to foster the exchange of innovative ideas and facilitate progress across this dynamic and transformative field.

The topics of this Special Issue include, but are not limited to, the following areas:

• Robot perception, recognition, guidance, navigation, mapping, and localization;
• Multi-robot task assignment and allocation;
• Bio-inspired neural networks, evolutionary computation, and artificial intelligence (AI);
• Learning-based robot decision, cooperation, environment, and situation understanding;
• Human–robot teaming and interaction.

Dr. Tingjun Lei
Dr. Chaomin Luo
Prof. Dr. Gene Eu Jan
Prof. Dr. Zhuming Bi
Guest Editors

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• robotics
• autonomous systems
• human–robot teaming and interaction
• bio-inspired artificial intelligence
• machine/deep learning