Motion Optimization and Control of Single and Multiple Autonomous Aerial, Land, and Marine Robots

Dear Colleagues,

Fast paced developments in the fields of aerial, land, and marine robotics have given impetus to a wide spectrum of scientific and commercial applications with far reaching societal implications. Autonomous robots equipped with advanced sensors and manipulators afford humans the capability to operate seamlessly in remote and hazardous environments, as if they were extensions of our eyes and hands. Robots have become the tools par excellence for scientists and commercial operators to explore and monitor the state of heterogenous environments on Earth, inspect wave and energy offshore infrastructures, monitor the growth of crops, and transport goods, among a myriad of other activities. Groups of robots acting in cooperation have started to impact the development of multiple system platforms for adaptive environmental sampling, search and rescue operations in hard to access regions, and even coordinate image-taking in the movie and sports industries. The types of robots used are highly heterogeneous and cater to specific user-defined requirements for operations in air, on land, and at sea. Notwithstanding this diversity, they have a number of attributes in common that are key to their capability to explore or act upon the environment with great agility while exhibiting high levels of performance, resilience, adaptability, and safety. 

It is against this backdrop of ideas that in this Special Issue we address fundamental problems that, in our opinion, are at the root of the development of a new breed of heterogenous robots that can act in isolation or cooperatively towards the execution of a wide spectrum of mission scenarios. Among such issues, we highlight the following: study of single and cooperative motion planning methods with a view to meeting temporal and energy constraints in the presence of robot dynamic constraints, while taking the topology of the underlying communication network and intervehicle and vehicle-obstacle avoidance requisites into account; creation of safe and emergent behaviours in a distributed manner, both at the motion planning and control levels, incorporating event-driven communication strategies to try and reduce the amount of information exchanged among the different agents; study of new methods to solve constrained optimal control problems efficiently in a receding horizon fashion; development of effective techniques for adaptive and robust control in the presence of plant model uncertainty of partially known models, especially for safety critical systems, using tools at the crossroads of reinforcement learning and feedback control; study of how advanced perception can be applied for the reformulation of the above problems in a sensor-based context, yielding challenging questions in the area of visual- and acoustic-based servoing, object tracking, and obstacle detection and avoidance.

Prof. Dr. Reza Ghabcheloo
Prof. Dr. Antonio M. Pascoal
Guest Editors

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