The target searching problem is a situation where a formation of multi-robot systems is set to search for a target and converge towards it when it is found. This problem lies in the fact that the target is initially absent and the formation must search for it in the environment. During the target search, false targets may appear dragging the formation towards it. Therefore, in order to avoid the formation following a false target, this paper presents a new methodology using the Takagi–Sugeno type fuzzy automaton (TS-TFA) in the area of formation control to solve the target searching problem. The TS fuzzy system is used to change the formation through the modifications in the states of the automaton. This change does not only switch the rules and therefore the state of each robot, but also the controllers and cost functions. This approach amplifies the versatility of the formation of mobile robots in the target searching problem. In this paper, the TS-TFA is presented and its implications in the formation are explained. Simulations and results with real robot are presented where it can be noticed that the formation is broken to maximize the perception range based on each robot’s observation of a possible target. Finally this work is concluded in the last section.
Intelligent state changing applied to multi-robot systems
BONARINI, ANDREA
2012-01-01
Abstract
The target searching problem is a situation where a formation of multi-robot systems is set to search for a target and converge towards it when it is found. This problem lies in the fact that the target is initially absent and the formation must search for it in the environment. During the target search, false targets may appear dragging the formation towards it. Therefore, in order to avoid the formation following a false target, this paper presents a new methodology using the Takagi–Sugeno type fuzzy automaton (TS-TFA) in the area of formation control to solve the target searching problem. The TS fuzzy system is used to change the formation through the modifications in the states of the automaton. This change does not only switch the rules and therefore the state of each robot, but also the controllers and cost functions. This approach amplifies the versatility of the formation of mobile robots in the target searching problem. In this paper, the TS-TFA is presented and its implications in the formation are explained. Simulations and results with real robot are presented where it can be noticed that the formation is broken to maximize the perception range based on each robot’s observation of a possible target. Finally this work is concluded in the last section.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
