Flex Conference (Physical / Digital)

International Conference on Mathematical Models in Robotics and Automation - (ICMMRA-27)

8th - 9th May 2027 , Sydney - Australia

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Call For Papers

The (ICMMRA-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Mathematical Modeling are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Mathematical models in robotics applications
  • Optimization techniques for robotic systems
  • Stochastic modeling in robotic navigation
  • Mathematical frameworks for motion planning
  • Modeling robot perception and cognition
  • Data-driven approaches in robotics research
  • Mathematical modeling of robotic manipulation
  • Simulation of multi-robot systems dynamics
  • Mathematical approaches to human-robot interaction
  • Modeling the impact of AI in robotics
  • Mathematical frameworks for robotic control systems
  • Optimization in robotic design processes
  • Mathematical models for autonomous systems
  • Simulation of robotic task execution
  • Mathematical analysis of robotic performance
  • Modeling the effects of environment on robots
  • Mathematical frameworks for swarm robotics
  • Data-driven modeling in robotic learning
  • Mathematical approaches to robotic safety
  • Modeling the future of robotics technologies

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.