Abstract
Many bio-inspired coordination strategies have been investigated for swarm robots. Bacterial chemotaxis exhibits a certain degree of intelligence, and has been developed some optimization algorithm for robot(s), e.g., bacterial foraging optimization algorithm (BFOA) and bacterial colony chemotaxis optimization algorithm (BCC). This paper proposes a bacterial chemotaxis-inspired coordination strategy (BCCS) of swarm robotic systems for coverage and aggregation. The coverage is the problem of finding a solution to uniformly deploy robots on a given bounded space. To solve this problem, this paper uses chaotic preprocessing to generate the initial positions of the robots. After the initialization, each robot calculates the area only covered by itself as the fitness function value. Then, each robot makes an action, running or rotating, depending on coordination strategy inspired bacterial chemotaxis. Moreover, we extend this solution and introduce a random factor to overcome aggregation, which is to guide robots to rendezvous at an unspecified point. The simulation results demonstrate the superior performance of the proposed coordination strategy in both success rate and an average number of iterations than other controllers.
Highlights
Introduction and Aggregation of Swarm RobotsThe adaption behavior of biological creatures provides a source of inspiration for the coordination of robots
bacterial chemotaxis-inspired coordination strategy (BCCS) and A1 are compared with the bacteria-inspired controller in Reference [27], where A1 is the BCCS without chaotic preprocessing
All simulation results are probabilistic for two methods, we find the superiority of BCCS through some simulations
Summary
The adaption behavior of biological creatures provides a source of inspiration for the coordination of robots. Chemotaxis behavior in response to the presence of chemical concentration gradients occurs during foraging and has inspired a number of research and applications in robotic systems. The simplest microorganism with chemotaxis behavior is a bacterium. We focus on a simple bacterium called Escherichia coli (E. coli) and E. coli-inspired coordination strategies for robots. In foraging, E. coli performs a biased random walk, which is called bacterial chemotaxis [8]. Each bacterium moves to the highest (lowest) concentration location of the stimulus source based on the comparison between previous memory concentration and the current ones. It is likely that most of the time, the bacteria exhibit swarming behavior through interactions.
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