## 3 Networked Mobile Robot System Design Issues
### Scalability  
Scalability is one of the desired characteristics of robot networks. A robot network control strategy can be called scalable if the performance of the system does not decay by increasing the number of robots in the network. Existing networked robot research has only focused on small teams comprised of 5-10 robots. These networks have to be extended into large multi-robot teams in order to increase the system performance and generate more robust solutions. Although simulation studies have been considered as a valid methodology, constructing reliable scalable mobile robots for developing simple, robust, efficient and low-cost robot platforms is crucial for accomplishing scalable real world robotic research [83, 84, 85, 86]. [PERSON] _et al._[83] presented a potential field based distributed solution to the area coverage problem by using a mobile sensor network in an unknown environment. In this approach, robot units cooperatively work to cover the entire mission space by changing their initial configurations. This proposed method considers robot units as virtual particles where each of them is subject to virtual forces acting on each robot unit while being only dependent on the position and orientation of nearby robots and obstacles. This force is used as a control vector for each robot's motors. Robot units use only local information for decision-making, so there is no need for communication between robots. In this way, there is no need for environment modeling or localization. Hence the given methodology is highly scalable to large robot groups and the validity of the algorithm is demonstrated on a 100 robot deployment problem in a large and complex environment. [PERSON] and [PERSON] [84] presented a scalable multi-robot formation control solution for homogenous large robot teams. Their method is based on a new class of potential functions, which are inspired from crystal molecules. At each time step, robots calculate a vector indicating the robot's navigation direction using parameters such as static obstacles, formation maintenance, movement to the given common goal and movement to the unit center. Each robot navigates towards a goal direction only with the help of location information of the nearby robots, so this given solution is completely scalable to large robot groups. Nowadays, there has been remarkable research on human-robot interaction where scalability of the robots to the interaction in question has been a serious concern. Researchers have tried to develop systems to allow more effective communication between humans and robots in the education, rehabilitation, and museum tour applications with scalable tasks adaptive to interactions. [PERSON] _et al._[85] proposed a scalable interaction infrastructure for the human-robot interaction problem. This infrastructure consists of two characteristics phases: one of many-to-many interactions and the second of one-to-one interactions. The first phase is required to expose robot services to human beings and the second one takes place in the level of personal one-to-one interaction. The proposed approach allows many humans to interact with many robots by dividing requests while also undertaking one-to-one interactions. Although multi-robot and multi-person systems are introduced by [PERSON] _et al._ much of the current work is focused only upon single robots and single human beings and scalable approaches for human-robot interaction is still an open area of research. Reconfigurable modular robots also need scalability capability, because scalability provides high level task accomplishment capability to the robot with the help of a large number and complex modules. [PERSON] _et al._[86] constructed a reconfigurable modular robot called M-TRAN. The proposed mechanism can perform flexible and adaptable locomotion by acting as a four-legged robot or a snake-like one. Developments of local infrared communication between neighboring units and of parallel distributed motion control mechanisms make this method highly scalable, thus adaptable and dexterous.