The 7th edition of the International Conference on Cloud and Robotics (ICCR 2023 - https://cloudrobotics.info) will be held on March 06 2023 in Paris, France.
The domain of cloud robotics aims to converge robots with computation, storage and communication resources provided by the cloud. The cloud may complement robotic resources in several ways, including crowd-sourcing knowledge databases, context information, computational offloading or data-intensive information processing for artificial intelligence. Today, the paradigms of cloud/fog/edge computing propose software architecture solutions for robots to share computations or offload them to ambiant and networked resources. Yet, combining distant computations with the real time constraints of robotics is very challenging. As the challenges in this domain are multi-disciplinary and similar in other research areas, Cloud Robotics aims at building bridges among experts from academia and industry working in different fields, such as robotics, cyber-physical systems, automotive, aerospace, machine learning, artificial intelligence, software architecture, big data analytics, Internet-of-Things, networked control and distributed cloud systems.
The conference is organizing two special sessions: one on Robotics in Medicine, as well as one industry session.
Topics of interest include, but are not necessarily limited to:
Architectures and middleware solutions for cyber-physical systems, integrating the IoT, the cloud/fog/edge with robots and other actuators.
Software engineering practices for networked robotic and cyber-physical systems.
Domain Specific Languages for cloud robotics and cyber-physical systems.
Multi-robot coordination and orchestration.
Cloud/Fog/Edge-based control systems, possibly using deterministic wireless or wired networking.
Networked control with application to cloud/fog/edge robotic and cyber-physical systems.
Computational offloading and load balancing in robotics.
Distributed sensing, planning and actuation.
Distributed sensor fusion for improved control policies.
Self-adaptive networked cyber-physical and robotic systems.
Cloud-supported collective knowledge and parameter sharing between actuation systems.
Transfer and shared learning between tasks or across robotic systems.
Hands-on experiences and use cases in the fields of manufacturing, Industry 4.0, healthcare, active assisted living, logistics and transportation, security and surveillance, precision agriculture, smart grids, smart cities and others.