From drones to self-driving cars, robots and multi-robot systems are becoming pervasive in our daily lives. The incoming robotics revolution will fundamentally change the type of devices available to the general public. In contrast to the current concept of `smart' devices, which are capable of sensing and computation, robots are devices that integrate sensing, computation, and actuation in the physical world. An inescapable consequence of this introduction of robotics into our daily lives is the fact that these devices will be networked, will be heterogeneous in terms of capabilities, and will need to coordinate in teams to achieve complex tasks. The development of the Internet-of-Things is speeding up this process, and multi-robot systems will be used in many areas. Examples of such applications are search and rescue operations, industrial and agricultural inspection, coordinated vehicle platooning, space exploration, and medical or surgical activities. We envision a world where a designer can specify the behavior of heterogeneous groups of robots, and package this behavior in an application that can be installed on multiple robotic systems.
While it seems natural to deal with robot teams (“swarms”) as yet another instance of a classical distributed system, important aspects set the former apart from the latter. The dynamics of robot swarms are characterized by an inseparable mixture of spatial and network aspects. Spatial aspects include the fact that robots move, and modify their surrounding environment, while network aspects include a communication modality based on range-limited, gossip-based message passing, and an ever changing topology due to robot navigation across the environment. As a result, the mapping between swarm-level requirements and individual actions is a problem whose solution exceeds current approaches to distributed system design. Designing and developing swarm behaviors is achieved today through a slow trial-and-error process, in which the expertise of the designer and his or her ability to encode complex behaviors are the main factors for success. As a result, very few collaborative or emerging behaviors are actually used in practical robotic applications. While this is bound to change, new methods and techniques are required to alleviate the burden of the designer and allow the development, analysis, and optimization of large-scale collaborative multi-robot applications.
This Research Topic calls for contributions that illustrate and discuss innovative methods and technologies that will allow researchers and practitioners to design, test, and verify multi-robot behaviors at the scale required by real-world applications. This includes the development of new languages that set the designer at the appropriate abstraction level for swarm robotics, techniques for the deployment of software across hundreds if not thousands of robots, methods for debugging and verification methods of distributed robotic systems, and algorithms for consensus and decision making.
In summary, this Research Topic calls for contributions that can push forward our understanding of how multi-robot applications should be designed, developed, and optimized.
From drones to self-driving cars, robots and multi-robot systems are becoming pervasive in our daily lives. The incoming robotics revolution will fundamentally change the type of devices available to the general public. In contrast to the current concept of `smart' devices, which are capable of sensing and computation, robots are devices that integrate sensing, computation, and actuation in the physical world. An inescapable consequence of this introduction of robotics into our daily lives is the fact that these devices will be networked, will be heterogeneous in terms of capabilities, and will need to coordinate in teams to achieve complex tasks. The development of the Internet-of-Things is speeding up this process, and multi-robot systems will be used in many areas. Examples of such applications are search and rescue operations, industrial and agricultural inspection, coordinated vehicle platooning, space exploration, and medical or surgical activities. We envision a world where a designer can specify the behavior of heterogeneous groups of robots, and package this behavior in an application that can be installed on multiple robotic systems.
While it seems natural to deal with robot teams (“swarms”) as yet another instance of a classical distributed system, important aspects set the former apart from the latter. The dynamics of robot swarms are characterized by an inseparable mixture of spatial and network aspects. Spatial aspects include the fact that robots move, and modify their surrounding environment, while network aspects include a communication modality based on range-limited, gossip-based message passing, and an ever changing topology due to robot navigation across the environment. As a result, the mapping between swarm-level requirements and individual actions is a problem whose solution exceeds current approaches to distributed system design. Designing and developing swarm behaviors is achieved today through a slow trial-and-error process, in which the expertise of the designer and his or her ability to encode complex behaviors are the main factors for success. As a result, very few collaborative or emerging behaviors are actually used in practical robotic applications. While this is bound to change, new methods and techniques are required to alleviate the burden of the designer and allow the development, analysis, and optimization of large-scale collaborative multi-robot applications.
This Research Topic calls for contributions that illustrate and discuss innovative methods and technologies that will allow researchers and practitioners to design, test, and verify multi-robot behaviors at the scale required by real-world applications. This includes the development of new languages that set the designer at the appropriate abstraction level for swarm robotics, techniques for the deployment of software across hundreds if not thousands of robots, methods for debugging and verification methods of distributed robotic systems, and algorithms for consensus and decision making.
In summary, this Research Topic calls for contributions that can push forward our understanding of how multi-robot applications should be designed, developed, and optimized.
