Intelligent Robotics and Autonomous Systems for Challenging Environments

Dear Colleagues,

Challenging environments are generally referred to as environments which are unknown, unstructured, dynamic, cluttered, hazardous, expansive, or resource-constrained (such as lack of GPS and communications and hindered visibility).

The development of robotic and autonomous systems (RAS) for these environments is an ongoing challenge. Many traditional RAS are inadequate because the interactions between the RAS and the environment can be critical for success, complex and difficult to model, or simply unpredictable and constantly changing.

Intelligent robotics and autonomous systems (iRAS) are playing an increasingly important role in challenging and extreme environments that are physically remote, unreachable or dangerous for humans.  As such, iRAS are often deployed in place of humans and must have greater capabilities to fulfil their roles than systems that can work alongside humans. To date, a diverse range of robotic technologies have been developed for challenging environment applications that include agriculture, nuclear maintenance and decommissioning, search and rescue operations, planetary exploration and undersea mapping, monitoring, and intervention.  However, we are still far from an era where robots will possess sufficient levels of intelligence and autonomy to perform tasks fully unsupervised and with human-level skills in these environments.

Noting that many of these technologies are transferable across applications, the motivation behind this Special Issue is to bring together key robotic technologies from differing fields to inspire new ideas for more generalised solutions from existing application-specific technologies. The issue is calling for cutting-edge contributions to fundamental research in the area of iRAS and ground-breaking applications  in industries.

The SI welcomes topics including but not limited to:

• Space robotics
• Aerial robotics
• Underwater robotics
• Agriculture robotics
• Medical robotics
• Nuclear robotics
• Adaptable and reconfigurable robotics
• Design and system modelling
• Intelligent control
• Intelligent sensing
• Perception and reasoning
• Digital twinning
• Sensor fusion
• Computation vision
• Machine learning including deep learning
• Autonomy and self-management
• Kinematics and dynamics
• Motion control and path planning
• Intelligent navigation

Dr. Mark A. Post
Dr. Erfu Yang
Prof. Dr. Gokhan Inalhan
Guest Editors

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