The Internet of Robotic Things (IoRT), the combination of robotics with the manipulation/interaction/perception/motion ability in the physical world and Internet of Things (IoT) with the realization ability of independent and smart networks, is bringing us unprecedented insight and applications in truly autonomous networks globally in homes, offices, smart cities, and more. Humanoid robots can provide professional service by mimicking human motion and interaction, and its market should grow from $2.1 billion in 2020 to $7.9 billion by 2025, at a compound annual growth rate (CAGR) of 30.6% for the period of 2020-2025. The rapid expansion of the humanoid robot market is driven by the integration of humanoid robots with various technologies and increasing adoption of high-speed networking technologies, such as edge computing, cloud computing, fog computing, cloud robotics, and AI in IoRT, in increasing numbers of application areas. Moreover, edge intelligence is introduced into humanoid robots to monitor events, fuse sensor data from the environment, make robust decision of action, and then recognize /manipulate physical objects, and more, under the support of IoRT. Furthermore, IoRT-enabled edge intelligence brings technological advantages in humanoid robots, and robot cognition is committed to developing learning algorithms such as deep learning and reinforcement learning to help robots autonomously learn from the physical world in a continuous way.

However, there are challenges yet to be addressed in the cognition of humanoid robots, such as the unreliable cognitive capacity among IoRT entities due to big data computing and caching, and the unreliable cognitive progress of artificial intelligence for truly intelligent robots. Moreover, it is necessary to accelerate the intelligent cognitive assistant human-robot cooperation via the harnessing of edge intelligence to enhance robotic cognition and physical capabilities for interacting with new cyber-physical systems, optimizing the human-robot interface, and other activities.

The aim of this Special Issue is to collate original research and review articles describing advances in this field.

Potential topics include but are not limited to the following:

• Edge intelligent humanoid cognitive robots based on IoRT
• Autonomous humanoid robot networks
• Edge intelligence-aided autonomous humanoid robots
• Optimal schedule of networked humanoid robots
• Testbeds and benchmarks to evaluate and compare research frameworks
• Self-organizing coordination and communication of humanoid robots based on IoRT
• Communication protocols for intelligent robotic networks
• Edge intelligent cognitive systems for humanoid robotics
• Simultaneous localization and mapping (SLAM) for intelligent humanoid robotics
• Trajectory scheduling and target tracking of humanoid robotics
• Wireless charging for autonomous humanoid robots
• Cognitive resource allocation among humanoid robotics
• Learning and autonomous control of humanoid robotics
• Edge intelligent human-robot interactions
• Privacy and security in IoRT-based humanoid robotics