## 1 Introduction
### Conclusions  
Some conclusions arise from this brief survey of recent works. Firstly, it is remarkable that despite being the most restrictive class of exploration algorithms, the exploration strategies based on continuous connectivity are prevalent in applications where real-time image streaming are needed (e.g., search and rescue), or simply when human operators at the base station need to enforce timely information updates, or even when a high level of coordination is needed (i.e., when globally shared knowledge between robots is assumed). Additionally, robustness is also highly appreciated in hostile or inaccessible scenarios. In these missions, fault-tolerance is typically achieved adding redundancy (e.g., systems that guarantee k-connected time-varying network topologies) and employing distributed systems.  
Nevertheless, when these strong requirements do not condition the mission, the event-based connectivity--that is less restrictive than the former concerning the fleet mobility--seems to be more appropriate.  
Now, moving up from essential aspects as communication to the top of the software architecture stack. There exists a large set of distributed reactive and behaviour-based proposals. Compared to the centralised approaches, distributed approaches have the advantage of not presenting the single-point-of-failure weakness. However, in many cases, it suffers from deadlocks at the individual or collective level.  
Market-based coordination methods represent another popular option. There exists a wide variety of implementations that mainly differ from each other in the way the bids are computed by the robots (e.g., single-item or multiple-item auctions). These difference are not insignificant and typically trade simplicity and computational efficiency off for proper coordination and local optima avoidance. Besides, since each auction involves a period of synchronicity between robots, fully asynchronous market-based systems have no place. Nevertheless, asynchronous systems may be advantageous over those that periodically ask the robots to wait for others before making a decision.  
Finally, in communication-restricted environments, there seems to be a general agreement on the benefits of spreading out the fleet as long as the robots can regain connectivity in disconnection case. From this, and trying to balance these potentially opposed goals, some multi-objective utility-based approaches have been proposed. Also, defining multiple roles (including communication relays) has demonstrated to be a worthy strategy to address the multi-robot exploration problem when communication restrictions are present.  
In conclusion, the survey suggests that in the context of decentralised systems there is room to try new ideas related to connectivity-regaining policies and rendezvous places. On the one hand, the event-based connectivity framework imposes the execution of connectivity-regaining actions in the presence of some events. On the other hand, rendezvous-based approaches imply the definition of particular meeting points where robots have to meet in order to regain connectivity. Leaving apart the fact that the selection of these places could be a hard issue itself, once the connectivity-regaining action is triggered and the meeting place is known by robots, they should interrupt its exploration plans deviating from its current trajectories in order to accomplish the new goal. This action probably leads to global time performance degradation and individual energy consumption increasing. However, what would happen if robots are only influenced to keep or recover connectivity at all times instead of being demanded to regain connectivity? Furthermore, what would happen if they are free to meet by chance, having been motivated to stay close but without having to meet at specific places?