## 1 Introduction
### Connectivity-Based Proposals
This technique takes advantage of local interaction and coordination from the interaction-oriented resolution of decentralised decision makers. _Distributed value functions (DVS)_ are used by decoupling the multi-agent problem into a set of individual agent problems. In order to address full local observability, limited information sharing, and communication breaks, an extension of the _DVS_ methodology is proposed and applied in multi-robot exploration so that each robot computes locally a strategy that minimises the interaction between fleet members and maximises the coverage achieved by the team, even in communication constrained environments. A decision step consists in building the model, computing the policy from the _DVS_ and producing a trajectory. Rendezvous-based techniques have also been used to deal with limited communication ranges. In [16] robots are enabled to move out of the communication range but forced to rejoin the group frequently. After moving out the communication range robots have to return to a pre-arranged meeting point to exchange the information gathered during the disconnection period in order to avoid exploration overlaps. The proposal presented in [29] describes a _Particle Swarm Optimisation_ based approach to achieving fault-tolerance in preventing communication network splits. The principal objective is to keep the fleet \(k\)-connected. Considering that the application domain defines the fault-tolerance level required to the system, a MANET connectivity algorithm is extended with the concept of \(k\)-fault-tolerance. A multi-robot system for crisis management is described in [30]. The system is composed of mobile sensors (ground robots--UGV) and mobile relays (aerial vehicles--UAV). However, some robots may change roles dynamically during the mission (e.g., UAVs equipped with both wireless routers and cameras). The problem is modelled and solved using constrained-based local search on a communication model based on graph theory. In [31] a fully distributed approach for multi-robot sweep exploration is introduced. The proposal aims to guarantee full coverage using a minimum number of messages and to maintain connectivity at all times, even under severe restrictions on the communication type, range, and quality. The algorithm proposed uses communication not only to exchange information but to direct the robot movements. Communication intensity is used in order to disperse the fleet while beacons are used to mark locations of interest. In [32] a multi-robot exploration algorithm based on multiple behaviours is proposed. Quad-rotors are asked to explore and map an indoor zone with unreliable communication and limited battery life. Robots are enabled to change roles both dynamically according to intrinsic and extrinsic factors (e.g., boundaries/distances and battery level) and hierarchically in order to explore and avoid collision among each other. The remaining battery level is considered in order to avoid losing gathered information. Quad-rotors are also able to leave the network, but after a fixed period they search for regaining connectivity. Relay robots are designated to forward information from/to the more distant robots improving communication between team members. Although no optimal relay placement is computed, the existence of relays is crucial in the proposed scheme. In [33; 34] the relay node dynamic re-positioning problem is tackled. The proposed solution relies on optimisation procedures and evolutionary algorithms to find the best relay locations and how the robots should move to these points. The authors follow a centralised multi-stage approach where one node is in charge of computing the best assignment regarding both connectivity and throughput. In [35], the problem of how to connect one or more remote units to a base station investing a limited number of intermediate relay robots in constrained communication environments is investigated.