While 5G and 6G networks continue to advance rapidly, remarkable progress has also been made in robotics. However, these two domains have largely advanced in isolation. In the emerging 6G era, encompassing applications such as future smart cities and smart factories, systems are expected to become increasingly complex, requiring the seamless integration of aerial, ground, and underwater robots with advanced wireless communications. The key challenge lies in effectively combining these areas to enable optimal orchestration, reliable service delivery, and large-scale use case deployments across diverse scenarios. Two complementary paradigms can be envisioned for such intelligent wireless networks: (i) network-aided robotics, where the communication infrastructure ensures safe, reliable control and monitoring of robots beyond visual line-of-sight; and (ii) robot-aided networks, where robots assist thThe main principles of future mobile communication systems are the ability to handle a higher degree of flexibility and functionality enabling future intelligent connectivity and control in a distributed manner along with co-resident communication and sensing: Moving away from traditional network architectures with passive nodes toward a ubiquitous intelligence, where native AI plays a prominent role to orchestrate different parts of the network from core to edge and to the cloud. In parallel, the 6G Radio Access Network (RAN) is evolving towards an Open and disaggregated architecture. 3GPP has surveyed and documented many functional splits in TR 38.801, leading toward the emergence of fully disaggregated RAN implementation. This evolution aligns with integrating robots into wireless networks, where each robot can act as a distributed node to assist the network. Despite the widespread applications of distributed networks and considerable attention received from academia and industry, integrating robots into distributed networks for collaborative learning and decision-making is still in its infancy. In particular, several challenges regarding the high communication overhead, modeling the behavior of robots in the presence of radio components, modeling robot-to-robot and robot-to-infrastructure radio links, and, in general, the performance and feasibility regarding the implementation and deployment of such networks are yet to be addressed.e communication infrastructure by extending coverage, enhancing sensing capabilities, and supporting accurate localization.

The main principles of future mobile communication systems are the ability to handle a higher degree of flexibility and functionality enabling future intelligent connectivity and control in a distributed manner along with co-resident communication and sensing: Moving away from traditional network architectures with passive nodes toward a ubiquitous intelligence, where native AI plays a prominent role to orchestrate different parts of the network from core to edge and to the cloud. In parallel, the 6G Radio Access Network (RAN) is evolving towards an Open and disaggregated architecture. 3GPP has surveyed and documented many functional splits in TR 38.801, leading toward the emergence of fully disaggregated RAN implementation. This evolution aligns with integrating robots into wireless networks, where each robot can act as a distributed node to assist the network. Despite the widespread applications of distributed networks and considerable attention received from academia and industry, integrating robots into distributed networks for collaborative learning and decision-making is still in its infancy. In particular, several challenges regarding the high communication overhead, modeling the behavior of robots in the presence of radio components, modeling robot-to-robot and robot-to-infrastructure radio links, and, in general, the performance and feasibility regarding the implementation and deployment of such networks are yet to be addressed.

Paper Submission Deadline: 18 January 2026, 31 January 2026 (extended)

Paper Acceptance Notification: 8 March 2026

Camera Ready: 22 March 2026

Submission link via EDAS: https://edas.info/N34751

For more details please check out the IEEE ICC 2026 website: https://icc2026.ieee-icc.org