# A Bacterial Chemotaxis-Inspired Coordination Strategy for Coverage and Aggregation of Swarm Robots
## 2 Bacteria Inspiration
### Applications  
In the past few decades, the focus of robotic system has shifted to applying biology-inspired methods. The bacterial chemotaxis-inspired coordination control methods have been studied in a single robot and multi-robot system. For a single robot, four reactive robot control algorithms based on chemotaxis are implemented and compared in Reference [17]. Among these algorithms, _E. coli_-based motion algorithm is the simplest and requires minimum structure and motion control requirements. However, it may only work with a very small system underground with steady changes of chemical concentrations. A Yuragi-based adaptive biased random walk strategy has been proposed to guide a mobile robot to locate a sound source in such an environment with and without gradient information [13]. This strategy can flexibly switch between the bacterial chemotaxis and Levy walk, which increases the success rate of the source search task. In Reference [14], a bacteria-inspired mobile robot, with a 1-DOF motor and a single sensor, has been proposed to navigate to a stimulus source, revealing the influence of environmental noise on navigation behavior. However, the related source searching algorithms based on bacterial chemotaxis cannot guarantee the repeatability of the path. Related bio-inspired coordination strategies have received attention in swarm robots. Because the complexity of the system increases with the number of individuals, the coordination model should be simple, effective, and scalability. Bacteria swarming is a relatively simple biological system compared to insect swarms, bird flocks, and fish schools. Hence,  
Figure 2: The basic behaviors of bacteria. it is the natural source of swarm robotic system design. In Reference [28], two novel chemotaxis-inspired controllers were proposed for controlling the formation of robots. This paper quantifies the achieved degree of preset formation of robots as a global index and decomposes it into local indexes, which are used by each robot at each step. There is evidence that the bacterial chemotaxis-inspired strategy can guide robots to search multiple sources [29]. In this approach, the robots take advantage of gradient information to execute a simple motion strategy (biased a random walk) inspired by bacterial chemotaxis. This is more suitable for boundary coverage, and multiple dissipative sources search tasks. A bacteria-inspired coordinate model for agents with adaptable interactions is proposed, which includes long-range attraction, intermediate-range alignment, and short-range repulsion [30]. This leads to a collective motion similar to bacteria swarming. Especially, agents can adjust the peers' influence depending on the number of their neighbors. A novel bacterial chemotaxis model has been introduced, which improved the average escape rate by reducing the tumbling frequency on obstacle-laden terrains [31]. Related extend work, distributed gradient descent (DGD), has been used for mass scale evacuations in a dynamic environment [32]. In the evacuation process, each agent combines messages and computations in a simple vocabulary, and the neighborhood graph of each agent is dynamic changes. In addition to the above motion coordination models, bacteria can also serve as inspiration for task allocation [33]. The performance of the proposed task allocation method has been proved to be better than the three traditional methods in the net throughput and runtime. Numerous researchers use bacteria-inspired methods for the coverage [5; 6; 7; 34; 35]. These methods mainly use robots to perform pollution visualization [5; 6; 7], and environmental exploration [34; 35]. However, the robots need the concentration information, which is not available in our hypothetical environment. Moreover, the research of the bio-inspired coordination strategies considering two or more tasks is insufficient. In Reference [35], a coordination strategy of swarm robots inspired by bacterial chemotaxis behavior is proposed for target search and trapping.